Zheng, Z.X.[Zhen-Xing],
Li, Z.D.[Zhen-Dong],
An, G.Y.[Gao-Yun],
Feng, S.H.[Song-He],
Subgraph and object context-masked network for scene graph generation,
IET-CV(14), No. 7, October 2020, pp. 546-553.
DOI Link
2010
BibRef
Xu, N.[Ning],
Liu, A.A.[An-An],
Wong, Y.K.[Yong-Kang],
Nie, W.Z.[Wei-Zhi],
Su, Y.T.[Yu-Ting],
Kankanhalli, M.[Mohan],
Scene Graph Inference via Multi-Scale Context Modeling,
CirSysVideo(31), No. 3, March 2021, pp. 1031-1041.
IEEE DOI
2103
Visualization, Context modeling, Proposals, Feature extraction,
Semantics, Head, Safety, Scene graph, context-fused inference,
multi-scale context
BibRef
Hung, Z.S.[Zih-Siou],
Mallya, A.[Arun],
Lazebnik, S.[Svetlana],
Contextual Translation Embedding for Visual Relationship Detection
and Scene Graph Generation,
PAMI(43), No. 11, November 2021, pp. 3820-3832.
IEEE DOI
2110
Visualization, Feature extraction, Task analysis, Training,
Semantics, Bicycles, Image edge detection,
scene understanding
BibRef
Zhou, H.[Hao],
Yang, Y.Z.[Ya-Zhou],
Luo, T.J.[Ting-Jin],
Zhang, J.[Jun],
Li, S.H.[Shuo-Hao],
A unified deep sparse graph attention network for scene graph
generation,
PR(123), 2022, pp. 108367.
Elsevier DOI
2112
Scene graph generation, Statistical co-occurrence knowledge,
Relationship measurement network, Graph attention network, Sparse graph
BibRef
Lin, B.Q.[Bing-Qian],
Zhu, Y.[Yi],
Liang, X.D.[Xiao-Dan],
Atom correlation based graph propagation for scene graph generation,
PR(122), 2022, pp. 108300.
Elsevier DOI
2112
Scene graph generation, Long-tailed distribution,
Knowledge graph, Atom correlation, Category space
BibRef
Li, P.[Ping],
Yu, Z.[Zhou],
Zhan, Y.B.[Yi-Bing],
Deep relational self-Attention networks for scene graph generation,
PRL(153), 2022, pp. 200-206.
Elsevier DOI
2201
Scene graph generation, Image understanding, Deep neural networks
BibRef
Wald, J.[Johanna],
Navab, N.[Nassir],
Tombari, F.[Federico],
Learning 3D Semantic Scene Graphs with Instance Embeddings,
IJCV(130), No. 3, March 2022, pp. 630-651.
Springer DOI
2203
BibRef
Garg, S.[Sarthak],
Dhamo, H.[Helisa],
Farshad, A.[Azade],
Musatian, S.[Sabrina],
Navab, N.[Nassir],
Tombari, F.[Federico],
Unconditional Scene Graph Generation,
ICCV21(16342-16351)
IEEE DOI
2203
Measurement, Image synthesis, Computational modeling,
Image edge detection, Semantics, Directed graphs, Neural generative models
BibRef
Tao, L.T.[Lei-Tian],
Mi, L.[Li],
Li, N.N.[Nan-Nan],
Cheng, X.H.[Xian-Hang],
Hu, Y.[Yaosi],
Chen, Z.Z.[Zhen-Zhong],
Predicate Correlation Learning for Scene Graph Generation,
IP(31), 2022, pp. 4173-4185.
IEEE DOI
2206
Correlation, Tail, Semantics, Head, Visualization,
Phase change materials, Optimization, Image understanding,
semantic overlap
BibRef
Luo, J.[Jie],
Zhao, J.[Jia],
Wen, B.[Bin],
Zhang, Y.H.[Yu-Hang],
Explaining the semantics capturing capability of scene graph
generation models,
PR(110), 2021, pp. 107427.
Elsevier DOI
2011
Explanation, Metrics, Semantic property, Scene graph generation,
Deep neural network
BibRef
Guo, Y.Y.[Yu-Yu],
Gao, L.L.[Lian-Li],
Song, J.K.[Jing-Kuan],
Wang, P.[Peng],
Sebe, N.[Nicu],
Shen, H.T.[Heng Tao],
Li, X.L.[Xue-Long],
Relation Regularized Scene Graph Generation,
Cyber(52), No. 7, July 2022, pp. 5961-5972.
IEEE DOI
2207
Visualization, Feature extraction, Task analysis, Semantics,
Detectors, Proposals, Convolution, visual relationship
BibRef
Zhao, B.[Bowen],
Mao, Z.D.[Zhen-Dong],
Fang, S.C.[Shan-Cheng],
Zang, W.Y.[Wen-Yu],
Zhang, Y.D.[Yong-Dong],
Semantically Similarity-Wise Dual-Branch Network for Scene Graph
Generation,
CirSysVideo(32), No. 7, July 2022, pp. 4573-4583.
IEEE DOI
2207
Visualization, Semantics, Feature extraction, Data mining, Encoding,
Message passing, Training, Scene graph generation, message propagating
BibRef
Lin, Z.Y.[Zhi-Yuan],
Zhu, F.[Feng],
Wang, Q.[Qun],
Kong, Y.Z.[Yan-Zi],
Wang, J.Y.[Jian-Yu],
Huang, L.[Liang],
Hao, Y.M.[Ying-Ming],
RSSGG_CS: Remote Sensing Image Scene Graph Generation by Fusing
Contextual Information and Statistical Knowledge,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Chang, X.J.[Xiao-Jun],
Ren, P.Z.[Peng-Zhen],
Xu, P.F.[Peng-Fei],
Li, Z.H.[Zhi-Hui],
Chen, X.J.[Xiao-Jiang],
Hauptmann, A.[Alex],
A Comprehensive Survey of Scene Graphs: Generation and Application,
PAMI(45), No. 1, January 2023, pp. 1-26.
IEEE DOI
2212
Survey, Graphs. Visualization, Task analysis, Feature extraction,
Image recognition, Cognition, Training, Systematics, Scene graph,
visual relationship recognition
BibRef
Han, X.J.[Xian-Jing],
Dong, X.N.[Xing-Ning],
Song, X.M.[Xue-Meng],
Gan, T.[Tian],
Zhan, Y.B.[Yi-Bing],
Yan, Y.[Yan],
Nie, L.Q.[Li-Qiang],
Divide-and-Conquer Predictor for Unbiased Scene Graph Generation,
CirSysVideo(32), No. 12, December 2022, pp. 8611-8622.
IEEE DOI
2212
Correlation, Image analysis, Task analysis,
Business process re-engineering, Predictive models,
Bayesian personalized ranking
BibRef
Han, X.J.[Xian-Jing],
Song, X.M.[Xue-Meng],
Dong, X.N.[Xing-Ning],
Wei, Y.W.[Yin-Wei],
Liu, M.[Meng],
Nie, L.Q.[Li-Qiang],
DBiased-P: Dual-Biased Predicate Predictor for Unbiased Scene Graph
Generation,
MultMed(25), 2023, pp. 5319-5329.
IEEE DOI
2311
BibRef
He, T.[Tao],
Gao, L.L.[Lian-Li],
Song, J.K.[Jing-Kuan],
Li, Y.F.[Yuan-Fang],
State-Aware Compositional Learning Toward Unbiased Training for Scene
Graph Generation,
IP(32), 2023, pp. 43-56.
IEEE DOI
2301
Visualization, Training, Task analysis, Predictive models, Dogs,
Standards, Genomics, Scene graph generation, feature decomposition,
data augmentation
BibRef
Wang, Y.[Yu],
Hu, L.[Liang],
Gao, W.[Wanfu],
Cao, X.F.[Xiao-Feng],
Chang, Y.[Yi],
AdaNS: Adaptive negative sampling for unsupervised graph
representation learning,
PR(136), 2023, pp. 109266.
Elsevier DOI
2301
Graph representation learning, Negative sampling, Noise contrastive estimation
BibRef
Zhou, H.[Hao],
Zhang, J.[Jun],
Luo, T.J.[Ting-Jin],
Yang, Y.Z.[Ya-Zhou],
Lei, J.[Jun],
Debiased Scene Graph Generation for Dual Imbalance Learning,
PAMI(45), No. 4, April 2023, pp. 4274-4288.
IEEE DOI
2303
Tail, Correlation, Training, Resistance, Visualization, Task analysis,
Semantics, Scene graph generation, dual imbalance learning,
context bias
BibRef
Li, X.[Xuewei],
Wu, T.[Tao],
Zheng, G.[Guangcong],
Yu, Y.L.[Yun-Long],
Li, X.[Xi],
Uncertainty-Aware Scene Graph Generation,
PRL(167), 2023, pp. 30-37.
Elsevier DOI
2303
Scene graph generation, Uncertainty analysis,
Bayesian classifier reparameterization
BibRef
Guo, X.J.[Xiao-Jie],
Zhao, L.[Liang],
A Systematic Survey on Deep Generative Models for Graph Generation,
PAMI(45), No. 5, May 2023, pp. 5370-5390.
IEEE DOI
2304
Computational modeling, Social networking (online), Reliability,
Biological system modeling, Taxonomy, Systematics, Semantics,
deep generative models for graphs
BibRef
Zhang, L.[Liang],
Yi, L.Q.[Long-Qiang],
Liu, Y.[Yu],
Wang, C.[Cheng],
Zhou, D.[Da],
Motif Entropy Graph Kernel,
PR(140), 2023, pp. 109544.
Elsevier DOI
2305
Graph representation, Motif entropy, Graph kernel, Wasserstein distance
BibRef
Wang, Z.[Zheng],
Xu, X.[Xing],
Luo, Y.[Yadan],
Wang, G.Q.[Guo-Qing],
Yang, Y.[Yang],
Hypercomplex context guided interaction modeling for scene graph
generation,
PR(141), 2023, pp. 109634.
Elsevier DOI
2306
Scene graph generation, Context guidence, Interaction modeling,
Hypercomplex embedding
BibRef
Wang, W.B.[Wen-Bin],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Importance First: Generating Scene Graph of Human Interest,
IJCV(131), No. 10, October 2023, pp. 2489-2515.
Springer DOI
2309
BibRef
Li, Y.M.[Yi-Ming],
Yang, X.S.[Xiao-Shan],
Huang, X.[Xuhui],
Ma, Z.[Zhe],
Xu, C.S.[Chang-Sheng],
Zero-Shot Predicate Prediction for Scene Graph Parsing,
MultMed(25), 2023, pp. 3140-3153.
IEEE DOI
2309
BibRef
Cong, Y.[Yuren],
Yang, M.Y.[Michael Ying],
Rosenhahn, B.[Bodo],
RelTR: Relation Transformer for Scene Graph Generation,
PAMI(45), No. 9, September 2023, pp. 11169-11183.
IEEE DOI
2309
BibRef
Cong, Y.[Yuren],
Liao, W.T.[Wen-Tong],
Ackermann, H.[Hanno],
Rosenhahn, B.[Bodo],
Yang, M.Y.[Michael Ying],
Spatial-Temporal Transformer for Dynamic Scene Graph Generation,
ICCV21(16352-16362)
IEEE DOI
2203
Visualization, Semantics, Neural networks, Genomics,
Transformer cores, Transformers, Video analysis and understanding
BibRef
Lyu, X.Y.[Xin-Yu],
Gao, L.L.[Lian-Li],
Zeng, P.P.[Peng-Peng],
Shen, H.T.[Heng Tao],
Song, J.K.[Jing-Kuan],
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation,
PAMI(45), No. 11, November 2023, pp. 13921-13940.
IEEE DOI
2310
BibRef
Lyu, X.Y.[Xin-Yu],
Gao, L.L.[Lian-Li],
Guo, Y.Y.[Yu-Yu],
Zhao, Z.[Zhou],
Huang, H.[Hao],
Shen, H.T.[Heng Tao],
Song, J.K.[Jing-Kuan],
Fine-Grained Predicates Learning for Scene Graph Generation,
CVPR22(19445-19453)
IEEE DOI
2210
Visualization, Head, Lattices, Tail, Benchmark testing,
Predictive models, Transformers, Visual reasoning
BibRef
Sun, S.[Shuzhou],
Zhi, S.[Shuaifeng],
Liao, Q.[Qing],
Heikkilä, J.[Janne],
Liu, L.[Li],
Unbiased Scene Graph Generation via Two-Stage Causal Modeling,
PAMI(45), No. 10, October 2023, pp. 12562-12580.
IEEE DOI
2310
BibRef
Liu, D.[Daqi],
Bober, M.[Miroslaw],
Kittler, J.V.[Josef V.],
Neural Belief Propagation for Scene Graph Generation,
PAMI(45), No. 8, August 2023, pp. 10161-10172.
IEEE DOI
2307
Task analysis, Belief propagation, Computational modeling,
Proposals, Message passing, Context modeling, Visualization,
variational approximation
BibRef
Liu, D.[Daqi],
Bober, M.[Miroslaw],
Kittler, J.V.[Josef V.],
Constrained Structure Learning for Scene Graph Generation,
PAMI(45), No. 10, October 2023, pp. 11588-11599.
IEEE DOI
2310
BibRef
Liu, D.[Daqi],
Bober, M.[Miroslaw],
Kittler, J.V.[Josef V.],
Importance Weighted Structure Learning for Scene Graph Generation,
PAMI(46), No. 2, February 2024, pp. 1231-1242.
IEEE DOI
2401
BibRef
Wang, Z.[Zheng],
Xu, X.[Xing],
Wang, G.Q.[Guo-Qing],
Yang, Y.[Yang],
Shen, H.T.[Heng Tao],
Quaternion Relation Embedding for Scene Graph Generation,
MultMed(25), 2023, pp. 8646-8656.
IEEE DOI
2312
BibRef
Yang, X.H.[Xu-Hua],
Ma, G.F.[Gang-Feng],
Ma, F.N.[Fang-Nan],
Ye, L.[Lei],
Zhang, Y.D.[Yu-Di],
Attribute network joint embedding based on global attention,
PRL(176), 2023, pp. 189-195.
Elsevier DOI Code:
WWW Link.
2312
Global attention mechanism, Convolutional neural network,
Structure embedding, Attribute embedding
BibRef
Pu, T.[Tao],
Chen, T.S.[Tian-Shui],
Wu, H.F.[He-Feng],
Lu, Y.Y.[Yong-Yi],
Lin, L.[Liang],
Spatial-Temporal Knowledge-Embedded Transformer for Video Scene Graph
Generation,
IP(33), 2024, pp. 556-568.
IEEE DOI
2401
Correlation, Visualization, Semantics, Transformers, Task analysis,
Prediction algorithms, Training, Video scene graph generation, language
BibRef
Chen, T.S.[Tian-Shui],
Yu, W.H.[Wei-Hao],
Chen, R.Q.[Ri-Quan],
Lin, L.[Liang],
Knowledge-Embedded Routing Network for Scene Graph Generation,
CVPR19(6156-6164).
IEEE DOI
2002
BibRef
Li, L.[Lin],
Xiao, J.[Jun],
Shi, H.[Hanrong],
Wang, W.X.[Wen-Xiao],
Shao, J.[Jian],
Liu, A.A.[An-An],
Yang, Y.[Yi],
Chen, L.[Long],
Label Semantic Knowledge Distillation for Unbiased Scene Graph
Generation,
CirSysVideo(34), No. 1, January 2024, pp. 195-206.
IEEE DOI
2401
BibRef
Lu, J.[Jiale],
Chen, L.G.X.[Liang-Gang-Xu],
Guan, H.Y.[Hao-Yue],
Lin, S.H.[Shao-Hui],
Gu, C.H.[Chun-Hua],
Wang, C.B.[Chang-Bo],
He, G.Q.[Gao-Qi],
Improving rare relation inferring for scene graph generation using
bipartite graph network,
CVIU(239), 2024, pp. 103901.
Elsevier DOI
2402
Text-supervised scene graph generation,
Bipartite graph network, Rare relation inferring
BibRef
Peng, Z.Z.[Zou-Zhang],
Zheng, S.[Shuai],
Zhu, Z.F.[Zhen-Feng],
Liu, Z.Z.[Zhi-Zhe],
Cheng, J.[Jian],
Dong, H.H.[Hong-Hui],
Zhao, Y.[Yao],
Graph meets probabilistic generation model:
A new perspective for graph disentanglement,
PR(148), 2024, pp. 110153.
Elsevier DOI Code:
WWW Link.
2402
Graph representation learning, Graph disentanglement,
Probabilistic generation model
BibRef
Qi, C.[Chao],
Yin, J.Q.[Jian-Qin],
Xu, J.H.[Jing-Hang],
Ding, P.X.[Peng-Xiang],
Instance-Incremental Scene Graph Generation From Real-World Point
Clouds via Normalizing Flows,
CirSysVideo(34), No. 2, February 2024, pp. 1057-1069.
IEEE DOI
2402
Task analysis, Point cloud compression, Layout, Semantics,
Feature extraction, Solid modeling,
point cloud
BibRef
Tang, Y.Q.[Yu-Qi],
Yang, X.[Xin],
Han, T.[Te],
Zhang, F.Y.[Fang-Yan],
Zou, B.[Bin],
Feng, H.H.[Hui-Hui],
Enhanced Graph Structure Representation for Unsupervised
Heterogeneous Change Detection,
RS(16), No. 4, 2024, pp. 721.
DOI Link
2402
BibRef
Zhang, Y.[Yong],
Pan, Y.W.[Ying-Wei],
Yao, T.[Ting],
Huang, R.[Rui],
Mei, T.[Tao],
Chen, C.W.[Chang-Wen],
End-to-End Video Scene Graph Generation With Temporal Propagation
Transformer,
MultMed(26), 2024, pp. 1613-1625.
IEEE DOI
2402
Transformers, Object detection, Feature extraction, Task analysis,
Detectors, Visualization, Video scene graph generation,
temporal propagation
BibRef
Chen, D.H.[Dong-Hua],
Zhang, R.T.[Run-Tong],
Building Multimodal Knowledge Bases With Multimodal Computational
Sequences and Generative Adversarial Networks,
MultMed(26), 2024, pp. 2027-2040.
IEEE DOI
2402
Build graph with deep learning.
Cognition, Generative adversarial networks, Data models,
Visualization, Feature extraction, Databases, multimodal data
BibRef
Liu, R.[Ruyue],
Yin, R.[Rong],
Liu, Y.[Yong],
Wang, W.P.[Wei-Ping],
Unbiased and Augmentation-Free Self-Supervised Graph Representation
Learning,
PR(149), 2024, pp. 110274.
Elsevier DOI
2403
Self-supervised, Representation learning, GNN, Pseudo-homology
BibRef
Zhao, M.N.[Meng-Nan],
Kong, Y.Q.[Yu-Qiu],
Zhang, L.[Lihe],
Yin, B.C.[Bao-Cai],
Class correlation correction for unbiased scene graph generation,
PR(149), 2024, pp. 110221.
Elsevier DOI Code:
WWW Link.
2403
Unbiased scene graph generation, Class correlation correction,
Debiasing transformation, Biasing transformation
BibRef
Li, X.[Xuewei],
Miao, P.[Peihan],
Li, S.Y.[Song-Yuan],
Li, X.[Xi],
MLMG-SGG: Multilabel Scene Graph Generation With Multigrained
Features,
IP(33), 2024, pp. 1549-1559.
IEEE DOI
2403
Pipelines, Feature extraction, Detectors, Image edge detection,
Task analysis, Visualization, Object detection,
multi-label classification
BibRef
Li, R.J.[Rong-Jie],
Zhang, S.Y.[Song-Yang],
He, X.M.[Xu-Ming],
SGTR+: End-to-End Scene Graph Generation With Transformer,
PAMI(46), No. 4, April 2024, pp. 2191-2205.
IEEE DOI
2403
BibRef
Earlier:
SGTR: End-to-end Scene Graph Generation with Transformer,
CVPR22(19464-19474)
IEEE DOI
2210
Visualization, Proposals, Task analysis, Transformers, Generators,
Decoding, Bipartite graph, deep learning, scene graph generation,
visual relationship detection.
Image analysis, Proposals, Visual reasoning
BibRef
Hayder, Z.[Zeeshan],
He, X.M.[Xu-Ming],
DSGG: Dense Relation Transformer for an End-to-End Scene Graph
Generation,
CVPR24(28317-28326)
IEEE DOI Code:
WWW Link.
2410
Training, Analytical models, Codes, Computational modeling,
Semantics, Benchmark testing, Scene graph generation,
Panoptic Scene Graph Generation
BibRef
Zheng, C.F.[Chao-Fan],
Gao, L.[Lianli],
Lyu, X.Y.[Xin-Yu],
Zeng, P.P.[Peng-Peng],
El Saddik, A.[Abdulmotaleb],
Shen, H.T.[Heng Tao],
Dual-Branch Hybrid Learning Network for Unbiased Scene Graph
Generation,
CirSysVideo(34), No. 3, March 2024, pp. 1743-1756.
IEEE DOI Code:
WWW Link.
2403
Tail, Head, Task analysis, Hybrid learning, DH-HEMTs, Visualization,
Schedules, Scene graph generation, vision and language, visual understanding
BibRef
Wu, H.[Hanrui],
Tian, L.[Lei],
Wu, Y.X.[Yan-Xin],
Zhang, J.[Jia],
Ng, M.K.[Michael K.],
Long, J.Y.[Jin-Yi],
Transferable graph auto-encoders for cross-network node
classification,
PR(150), 2024, pp. 110334.
Elsevier DOI
2403
Cross-network node classification, Transfer learning,
Domain adaptation, Graph auto-encoder, Graph convolutional network
BibRef
Yang, J.R.[Jia-Rui],
Wang, C.[Chuan],
Yang, L.[Liang],
Jiang, Y.C.[Yu-Chen],
Cao, A.[Angelina],
Adaptive Feature Learning for Unbiased Scene Graph Generation,
IP(33), 2024, pp. 2252-2265.
IEEE DOI
2404
Training, Tail, Representation learning, Message passing, Head,
Visualization, Aggregates, Unbiased scene graph generation,
feature enhancement
BibRef
Wei, W.W.[Wen-Wen],
Wei, P.[Ping],
Qin, J.[Jialu],
Liao, Z.M.[Zhi-Min],
Wang, S.[Shuaijie],
Cheng, X.[Xiang],
Liu, M.[Meiqin],
Zheng, N.N.[Nan-Ning],
3D Scene Graph Generation From Point Clouds,
MultMed(26), 2024, pp. 5358-5368.
IEEE DOI
2404
Feature extraction, Point cloud compression, Task analysis, Head,
Semantics, Proposals, 3D scene graph generation, point RoI,
point cloud
BibRef
Luo, T.Z.[Tian-Ze],
Mo, Z.F.[Zhan-Feng],
Pan, S.J.L.[Sinno Jia-Lin],
Fast Graph Generation via Spectral Diffusion,
PAMI(46), No. 5, May 2024, pp. 3496-3508.
IEEE DOI
2404
Computational modeling, Data models, Diffusion processes, Topology,
Mathematical models, Standards, Sparse matrices, Graph diffusion,
stochastic differential equations
BibRef
Wang, W.Q.[Wen-Qing],
Luo, Y.[Yawei],
Chen, Z.Q.[Zhi-Qing],
Jiang, T.[Tao],
Yang, Y.[Yi],
Xiao, J.[Jun],
Taking a Closer Look At Visual Relation: Unbiased Video Scene Graph
Generation With Decoupled Label Learning,
MultMed(26), 2024, pp. 5718-5728.
IEEE DOI
2404
Visualization, Tail, Task analysis, Head, Annotations,
Representation learning, Correlation, video scene graph generation (VidSGG)
BibRef
Lin, Z.H.[Zheng-Hong],
Yan, Q.S.[Qi-Shan],
Liu, W.M.[Wei-Ming],
Wang, S.P.[Shi-Ping],
Wang, M.H.[Meng-Han],
Tan, Y.C.[Yan-Chao],
Yang, C.[Carl],
Automatic Hypergraph Generation for Enhancing Recommendation With
Sparse Optimization,
MultMed(26), 2024, pp. 5680-5693.
IEEE DOI
2404
Optimization, Collaboration, Task analysis, Noise measurement,
Collaborative filtering, Electronic commerce,
graph convolutional network
BibRef
Dong, W.[Wei],
Yan, D.W.[Da-Wei],
Wang, P.[Peng],
Self-Supervised Node Representation Learning via
Node-to-Neighbourhood Alignment,
PAMI(46), No. 6, June 2024, pp. 4218-4233.
IEEE DOI
2405
Mutual information, Self-supervised learning,
Representation learning, Graph neural networks, Topology,
over-smoothing
BibRef
Dong, W.[Wei],
Wu, J.S.[Jun-Sheng],
Luo, Y.[Yi],
Ge, Z.Y.[Zong-Yuan],
Wang, P.[Peng],
Node Representation Learning in Graph via Node-to-Neighbourhood
Mutual Information Maximization,
CVPR22(16599-16608)
IEEE DOI
2210
WWW Link. Representation learning, Smoothing methods, Codes,
Computational modeling, Mutual information,
Self- semi- meta- unsupervised learning
BibRef
Wang, Z.H.[Zheng-Hao],
Lian, J.[Jing],
Li, L.H.[Lin-Hui],
Zhao, J.[Jian],
A Novel Framework for Scene Graph Generation via Prior Knowledge,
CirSysVideo(34), No. 5, May 2024, pp. 3768-3781.
IEEE DOI
2405
Feature extraction, Semantics, Visualization, Knowledge graphs, Tail,
Correlation, Scene graph generation, long-tailed, relation inference
BibRef
Huang, K.X.[Kai-Xiang],
Yang, J.[Jingru],
Wang, J.[Jin],
He, S.F.[Sheng-Feng],
Wang, Z.[Zhan],
He, H.Y.[Hai-Yan],
Zhang, Q.F.[Qi-Feng],
Lu, G.D.[Guo-Dong],
Granular3D: Delving into multi-granularity 3D scene graph prediction,
PR(153), 2024, pp. 110562.
Elsevier DOI
2405
3D point cloud, 3D semantic scene graph prediction,
Multi-granularity, Gather point transformer
BibRef
Xu, H.B.[Hong-Bo],
Wang, L.C.[Li-Chun],
Xu, K.[Kai],
Fu, F.Y.[Fang-Yu],
Yin, B.C.[Bao-Cai],
Huang, Q.M.[Qing-Ming],
A New Training Data Organization Form and Training Mode for Unbiased
Scene Graph Generation,
CirSysVideo(34), No. 7, July 2024, pp. 5295-5305.
IEEE DOI
2407
Training, Training data, Proposals, Tail, Semantics, Predictive models,
Head, Unbiased scene graph generation,
balanced predicate instances
BibRef
Liu, H.M.[Hui-Min],
Yang, Q.[Qiu],
Yang, X.X.[Xue-Xi],
Tang, J.B.[Jian-Bo],
Deng, M.[Min],
Gui, R.[Rong],
Coupling Hyperbolic GCN with Graph Generation for Spatial Community
Detection and Dynamic Evolution Analysis,
IJGI(13), No. 7, 2024, pp. 248.
DOI Link
2408
BibRef
Zhu, X.[Xuhan],
Wang, R.P.[Rui-Ping],
Lan, X.Y.[Xiang-Yuan],
Wang, Y.[Yaowei],
Local context attention learning for fine-grained scene graph
generation,
PR(156), 2024, pp. 110708.
Elsevier DOI
2408
Fine-grained scene graph generation, Local context,
Location attention network, Local context-consistent label transfer
BibRef
Liu, Z.H.[Zhi-Hong],
Wang, J.[Jianji],
Chen, H.[Hui],
Ma, Y.Q.[Yong-Qiang],
Zheng, N.N.[Nan-Ning],
Relation-Specific Feature Augmentation for unbiased scene graph
generation,
PR(157), 2025, pp. 110936.
Elsevier DOI
2409
Image understanding, Scene graph generation,
Long-tailed distribution, Feature augmentation
BibRef
Chu, K.C.[Kuan-Chao],
Yamazaki, S.[Satoshi],
Nakayama, H.[Hideki],
Enhanced Data Transfer Cooperating with Artificial Triplets for Scene
Graph Generation,
IEICE(E108-D), No. 9, September 2024, pp. 1239-1252.
WWW Link.
2410
BibRef
Zhang, R.N.[Ruo-Nan],
An, G.[Gaoyun],
Hao, Y.Q.[Yi-Qing],
Wu, D.P.O.[Da-Peng Oliver],
Bridging Visual and Textual Semantics:
Towards Consistency for Unbiased Scene Graph Generation,
PAMI(46), No. 11, November 2024, pp. 7102-7119.
IEEE DOI
2410
Semantics, Visualization, Cognition, Task analysis, Psychology,
Memory management, Genomics, Cross-modal alignment, visual reasoning
BibRef
Zhang, T.[Tong],
Liu, G.[Guangbu],
Cui, Z.[Zhen],
Liu, W.[Wei],
Zheng, W.M.[Wen-Ming],
Yang, J.[Jian],
Wasserstein Discriminant Dictionary Learning for Graph Representation,
PAMI(46), No. 12, December 2024, pp. 8619-8635.
IEEE DOI
2411
Dictionaries, Task analysis, Measurement, Machine learning, Topology,
Kernel, Vectors, Kron-Gromov-Wasserstein (KGW) metric,
wasserstein graph representation
BibRef
Wang, J.H.[Jing-Hao],
Wen, Z.Y.[Zheng-Yu],
Li, X.T.[Xiang-Tai],
Guo, Z.[Zujin],
Yang, J.K.[Jing-Kang],
Liu, Z.W.[Zi-Wei],
Pair Then Relation: Pair-Net for Panoptic Scene Graph Generation,
PAMI(46), No. 12, December 2024, pp. 10452-10465.
IEEE DOI
2411
Task analysis, Annotations, Pipelines, Decoding, Visualization,
Training, Sparse matrices, Detection transformer,
scene graph generation
BibRef
Liu, H.[Hengyue],
Bhanu, B.[Bir],
RepSGG: Novel Representations of Entities and Relationships for Scene
Graph Generation,
PAMI(46), No. 12, December 2024, pp. 8018-8035.
IEEE DOI
2411
Feature extraction, Visualization, Semantics, Task analysis,
Detectors, Shape, Training, Scene graph generation,
human-Object interaction
BibRef
Wang, L.[Lei],
Yuan, Z.[Zejian],
Lu, Y.[Yao],
Chen, B.D.[Ba-Dong],
Unbiased scene graph generation via head-tail cooperative network
with self-supervised learning,
IVC(151), 2024, pp. 105283.
Elsevier DOI Code:
WWW Link.
2411
Scene graph generation, Head-tail cooperative network,
Self-supervised learning, Unbiased
BibRef
Zhou, B.X.[Bing-Xin],
Li, R.[Ruikun],
Zheng, X.B.[Xue-Bin],
Wang, Y.G.[Yu Guang],
Gao, J.B.[Jun-Bin],
Graph Denoising With Framelet Regularizers,
PAMI(46), No. 12, December 2024, pp. 7606-7617.
IEEE DOI
2411
Convolution, Smoothing methods, Noise reduction, Noise, Transforms,
Wavelet transforms, spectral methods
BibRef
Lotfi, F.[Fariba],
Jamzad, M.[Mansour],
Beigy, H.[Hamid],
Farhood, H.[Helia],
Sheng, Q.Z.[Quan Z.],
Beheshti, A.[Amin],
Knowledge graph construction in hyperbolic space for automatic image
annotation,
IVC(151), 2024, pp. 105293.
Elsevier DOI
2411
Automatic image annotation, Attributed knowledge graph,
External knowledge sources, Hyperbolic space, Vision transformer
BibRef
Zhang, R.N.[Ruo-Nan],
An, G.[Gaoyun],
Cen, Y.G.[Yi-Gang],
Ruan, Q.Q.[Qiu-Qi],
Attention redirection transformer with semantic oriented learning for
unbiased scene graph generation,
PR(158), 2025, pp. 111039.
Elsevier DOI Code:
WWW Link.
2411
Scene graph generation, Transformer, Attention redirection,
Translation embedding, Scene understanding
BibRef
Wang, X.[Xu],
Li, Y.F.[Yi-Fan],
Zhang, Q.[Qiudan],
Wu, W.H.[Wen-Hui],
Li, M.J.J.[Mark Jun-Jie],
Ma, L.[Lin],
Jiang, J.M.[Jian-Min],
Weakly-Supervised 3D Scene Graph Generation via Visual-Linguistic
Assisted Pseudo-Labeling,
MultMed(26), 2024, pp. 11164-11175.
IEEE DOI
2412
Point cloud compression, Solid modeling, Visualization,
Annotations, Feature extraction, Training, weakly-supervised learning
BibRef
Tian, H.S.[Hong-Shuo],
Xu, N.[Ning],
Kankanhalli, M.[Mohan],
Liu, A.A.[An-An],
Gaussian Distribution-Aware Commonsense Knowledge Learning for Scene
Graph Generation,
CirSysVideo(34), No. 12, December 2024, pp. 13044-13057.
IEEE DOI
2501
Visualization, Commonsense reasoning, Uncertainty, Semantics, Noise,
Dogs, Legged locomotion, Scene graph generation,
dynamic routing
BibRef
Shi, H.R.[Han-Rong],
Li, L.[Lin],
Xiao, J.[Jun],
Zhuang, Y.T.[Yue-Ting],
Chen, L.[Long],
From Easy to Hard: Learning Curricular Shape-Aware Features for Robust
Panoptic Scene Graph Generation,
IJCV(133), No. 1, January 2025, pp. 489-508.
Springer DOI
2501
BibRef
Li, L.[Lin],
Chen, G.[Guikun],
Xiao, J.[Jun],
Yang, Y.[Yi],
Wang, C.P.[Chun-Ping],
Chen, L.[Long],
Compositional Feature Augmentation for Unbiased Scene Graph
Generation,
ICCV23(21628-21638)
IEEE DOI
2401
BibRef
Salzmann, T.[Tim],
Ryll, M.[Markus],
Bewley, A.[Alex],
Minderer, M.[Matthias],
Scene-graph VIT:
End-to-end Open-vocabulary Visual Relationship Detection,
ECCV24(LXXXIV: 195-213).
Springer DOI
2412
BibRef
Wang, L.[Lei],
Yuan, Z.[Zejian],
Chen, B.D.[Ba-Dong],
Multi-granularity Sparse Relationship Matrix Prediction Network for
End-to-end Scene Graph Generation,
ECCV24(LXXXII: 105-121).
Springer DOI
2412
BibRef
Peddi, R.[Rohith],
Singh, S.[Saksham],
Saurabh,
Singla, P.[Parag],
Gogate, V.[Vibhav],
Towards Scene Graph Anticipation,
ECCV24(LXXXVIII: 159-175).
Springer DOI
2412
BibRef
Chen, Z.[Zuyao],
Wu, J.L.[Jin-Lin],
Lei, Z.[Zhen],
Zhang, Z.X.[Zhao-Xiang],
Chen, C.W.[Chang Wen],
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph
Generation via Visual-concept Alignment and Retention,
ECCV24(LXVI: 108-124).
Springer DOI
2412
BibRef
Ma, Y.[Yanni],
Liu, H.[Hao],
Pei, Y.[Yun],
Guo, Y.L.[Yu-Lan],
Heterogeneous Graph Learning for Scene Graph Prediction in 3d Point
Clouds,
ECCV24(XXVI: 274-291).
Springer DOI
2412
BibRef
Zhang, C.Y.[Chao-Yi],
Yang, X.T.[Xi-Tong],
Hou, J.[Ji],
Kitani, K.[Kris],
Cai, W.D.[Wei-Dong],
Chu, F.J.[Fu-Jen],
EgoSG: Learning 3D Scene Graphs from Egocentric RGB-D Sequences,
SG2RL24(2535-2545)
IEEE DOI
2410
Point cloud compression, Accuracy, Semantics,
Reconstruction algorithms, Cameras, Prediction algorithms,
3D Scene Understanding
BibRef
Fischer, T.[Tobias],
Porzi, L.[Lorenzo],
Bulň, S.R.[Samuel Rota],
Pollefeys, M.[Marc],
Kontschieder, P.[Peter],
Multi-Level Neural Scene Graphs for Dynamic Urban Environments,
CVPR24(21125-21135)
IEEE DOI
2410
Training, Geometry, Art, Urban areas, Benchmark testing,
Rendering (computer graphics),
Scene Graph
BibRef
Rodin, I.[Ivan],
Furnari, A.[Antonino],
Min, K.[Kyle],
Tripathi, S.[Subarna],
Farinella, G.M.[Giovanni Maria],
Action Scene Graphs for Long-Form Understanding of Egocentric Videos,
CVPR24(18622-18632)
IEEE DOI Code:
WWW Link.
2410
Codes, Annotations, Manuals, Benchmark testing, Cameras,
egocentric vision, scene graphs, long-form video understanding
BibRef
Lorenz, J.[Julian],
Schön, R.[Robin],
Ludwig, K.[Katja],
Lienhart, R.[Rainer],
A Review and Efficient Implementation of Scene Graph Generation
Metrics,
SG2RL24(2567-2575)
IEEE DOI Code:
WWW Link.
2410
Measurement, Solid modeling, Reviews, Web services,
Computational modeling, scene graph, benchmark server,
metrics
BibRef
Wang, G.[Guan],
Li, Z.M.[Zhi-Min],
Chen, Q.C.[Qing-Chao],
Liu, Y.[Yang],
OED: Towards One-stage End-to-End Dynamic Scene Graph Generation,
CVPR24(27938-27947)
IEEE DOI Code:
WWW Link.
2410
Measurement, Visualization, Pipelines, Object detection,
Feature extraction, Aerodynamics, Trajectory
BibRef
Chen, L.G.X.[Liang-Gang-Xu],
Wang, X.J.[Xue-Jiao],
Lu, J.[Jiale],
Lin, S.H.[Shao-Hui],
Wang, C.B.[Chang-Bo],
He, G.[Gaoqi],
CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via
Cross-Modality Contrastive Learning,
CVPR24(27863-27873)
IEEE DOI
2410
Point cloud compression, Training, Annotations,
Contrastive learning, Feature extraction,
Contrastive Learning
BibRef
Im, J.[Jinbae],
Nam, J.[JeongYeon],
Park, N.[Nokyung],
Lee, H.[Hyungmin],
Park, S.H.[Seung-Hyun],
EGTR: Extracting Graph from Transformer for Scene Graph Generation,
CVPR24(24229-24238)
IEEE DOI Code:
WWW Link.
2410
Training, Adaptation models, Visualization, Smoothing methods,
Object detection, Detectors, Predictive models, self-attention
BibRef
Li, R.J.[Rong-Jie],
Zhang, S.Y.[Song-Yang],
Lin, D.[Dahua],
Chen, K.[Kai],
He, X.M.[Xu-Ming],
From Pixels to Graphs:
Open-Vocabulary Scene Graph Generation with Vision-Language Models,
CVPR24(28076-28086)
IEEE DOI
2410
Visualization, Vocabulary, Computational modeling,
Computer architecture, Cognition, Vision-language
BibRef
Zhang, C.[Ce],
Stepputtis, S.[Simon],
Campbell, J.[Joseph],
Sycara, K.[Katia],
Xie, Y.Q.[Ya-Qi],
HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph
Generation,
CVPR24(28233-28243)
IEEE DOI Code:
WWW Link.
2410
Training, Visualization, Snow, Perturbation methods, Genomics,
Benchmark testing, Prediction algorithms
BibRef
Li, J.[Jiankai],
Wang, Y.H.[Yun-Hong],
Guo, X.[Xiefan],
Yang, R.J.[Rui-Jie],
Li, W.X.[Wei-Xin],
Leveraging Predicate and Triplet Learning for Scene Graph Generation,
CVPR24(28369-28379)
IEEE DOI Code:
WWW Link.
2410
Visualization, Head, Triples (Data structure), Semantics, Genomics,
Tail
BibRef
Khandelwal, A.[Anant],
FloCoDe: Unbiased Dynamic Scene Graph Generation with Temporal
Consistency and Correlation Debiasing,
SG2RL24(2516-2526)
IEEE DOI
2410
Visualization, Correlation, Uncertainty, Dynamics, Performance gain,
Attenuation, Feature extraction
BibRef
Chacra, D.A.[David Abou],
Zelek, J.[John],
Naive Scene Graphs: How Visual is Modern Visual Relationship
Detection?,
CRV23(208-216)
IEEE DOI
2406
Visualization, Solid modeling, Refining, Object detection, Machine learning,
Predictive models, Scene Graph Generation, Statistical Approaches
BibRef
Wang, J.[Junyao],
Malawade, A.V.[Arnav Vaibhav],
Zhou, J.[Junhong],
Yu, S.Y.[Shih-Yuan],
Faruque, M.A.A.[Mohammad Abdullah Al],
RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust
Autonomous Perception and Scenario Understanding,
WACV24(7478-7487)
IEEE DOI
2404
Training, Deep learning, Navigation, Roads, Computational modeling,
Transfer learning, Transformers, Applications, Autonomous Driving,
Embedded sensing / real-time techniques
BibRef
Zang, Y.J.[Yu-Jie],
Li, Y.C.[Yao-Chen],
Gao, Y.[Yuan],
Guo, Y.[Yimou],
Tang, W.N.[Wen-Neng],
Li, Y.X.[Yan-Xue],
Atlaw, M.[Meklit],
Refine and Redistribute: Multi-Domain Fusion and Dynamic Label
Assignment for Unbiased Scene Graph Generation,
WACV24(1307-1316)
IEEE DOI
2404
Training, Adaptation models, Visualization,
Computer network reliability, Computational modeling,
Vision + language and/or other modalities
BibRef
Koch, S.[Sebastian],
Hermosilla, P.[Pedro],
Vaskevicius, N.[Narunas],
Colosi, M.[Mirco],
Ropinski, T.[Timo],
SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level
Scene Reconstruction,
WACV24(3392-3402)
IEEE DOI
2404
Solid modeling, Annotations, Semantics, Predictive models,
Data models, Algorithms, 3D computer vision, Algorithms
BibRef
Xu, B.[Bicheng],
Liao, R.J.[Ren-Jie],
Sigal, L.[Leonid],
Self-Supervised Relation Alignment for Scene Graph Generation,
WACV24(1328-1338)
IEEE DOI
2404
Visualization, Message passing, Image edge detection, Genomics,
Predictive models, Mirrors, Algorithms, Image recognition and understanding
BibRef
Han, Y.[Yan],
Wang, P.H.[Pei-Hao],
Kundu, S.[Souvik],
Ding, Y.[Ying],
Wang, Z.Y.[Zhang-Yang],
Vision HGNN: An Image is More than a Graph of Nodes,
ICCV23(19821-19831)
IEEE DOI Code:
WWW Link.
2401
BibRef
Marcu, A.[Alina],
Pirvu, M.[Mihai],
Costea, D.[Dragos],
Haller, E.[Emanuela],
Slusanschi, E.[Emil],
Belbachir, N.[Nabil],
Sukthankar, R.[Rahul],
Leordeanu, M.[Marius],
Self-supervised Hypergraphs for Learning Multiple World
Interpretations,
LIMIT23(983-992)
IEEE DOI
2401
BibRef
Thauvin, D.[Dao],
Herbin, S.[Stéphane],
Knowledge Informed Sequential Scene Graph Verification Using VQA,
SG2RL23(21-31)
IEEE DOI
2401
BibRef
Sudhakaran, G.[Gopika],
Dhami, D.S.[Devendra Singh],
Kersting, K.[Kristian],
Roth, S.[Stefan],
Vision Relation Transformer for Unbiased Scene Graph Generation,
ICCV23(21825-21836)
IEEE DOI
2401
BibRef
Yu, Q.F.[Qi-Fan],
Li, J.C.[Jun-Cheng],
Wu, Y.[Yu],
Tang, S.L.[Si-Liang],
Ji, W.[Wei],
Zhuang, Y.T.[Yue-Ting],
Visually-Prompted Language Model for Fine-Grained Scene Graph
Generation in an Open World,
ICCV23(21503-21514)
IEEE DOI
2401
BibRef
Min, Y.[Yukuan],
Wu, A.[Aming],
Deng, C.[Cheng],
Environment-Invariant Curriculum Relation Learning for Fine-Grained
Scene Graph Generation,
ICCV23(13250-13261)
IEEE DOI
2401
BibRef
Mlodzian, L.[Leon],
Sun, Z.G.[Zhi-Gang],
Berkemeyer, H.[Hendrik],
Monka, S.[Sebastian],
Wang, Z.X.[Zi-Xu],
Dietze, S.[Stefan],
Halilaj, L.[Lavdim],
Luettin, J.[Juergen],
nuScenes Knowledge Graph - A comprehensive semantic representation of
traffic scenes for trajectory prediction,
SG2RL23(42-52)
IEEE DOI Code:
WWW Link.
2401
BibRef
Holm, F.[Felix],
Ghazaei, G.[Ghazal],
Czempiel, T.[Tobias],
Özsoy, E.[Ege],
Saur, S.[Stefan],
Navab, N.[Nassir],
Dynamic Scene Graph Representation for Surgical Video,
SG2RL23(81-87)
IEEE DOI
2401
BibRef
Farshad, A.[Azade],
Yeganeh, Y.[Yousef],
Chi, Y.[Yu],
Shen, C.Z.[Cheng-Zhi],
Ommer, B.[Björn],
Navab, N.[Nassir],
SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis,
SG2RL23(88-98)
IEEE DOI
2401
BibRef
Neau, M.[Maëlic],
Santos, P.E.[Paulo E.],
Bosser, A.G.[Anne-Gwenn],
Buche, C.[Cédric],
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for
Efficient Scene Graph Generation,
SG2RL23(11-20)
IEEE DOI
2401
BibRef
Zhao, C.Y.[Cheng-Yang],
Shen, Y.[Yikang],
Chen, Z.F.[Zhen-Fang],
Ding, M.Y.[Ming-Yu],
Gan, C.[Chuang],
TextPSG: Panoptic Scene Graph Generation from Textual Descriptions,
ICCV23(2827-2838)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zhou, Z.J.[Zi-Jian],
Shi, M.J.[Miao-Jing],
Caesar, H.[Holger],
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic
Scene Graph Generation,
ICCV23(21580-21591)
IEEE DOI Code:
WWW Link.
2401
BibRef
Lorenz, J.[Julian],
Barthel, F.[Florian],
Kienzle, D.[Daniel],
Lienhart, R.[Rainer],
Haystack: A Panoptic Scene Graph Dataset to Evaluate Rare Predicate
Classes,
SG2RL23(62-70)
IEEE DOI Code:
WWW Link.
2401
BibRef
Sun, S.Q.[Shi-Qi],
Huang, D.[Danlan],
Qin, Z.J.[Zhi-Jin],
Tao, X.M.[Xiao-Ming],
Pan, C.[Chengkang],
Liu, G.Y.[Guang-Yi],
USGG: Union Message Based Scene Graph Generation,
ICIP23(2575-2579)
IEEE DOI
2312
BibRef
Chen, J.[Jie],
Li, Z.L.[Zi-Long],
Zhu, Y.[Yin],
Zhang, J.P.[Jun-Ping],
Pu, J.[Jian],
From Node Interaction to Hop Interaction:
New Effective and Scalable Graph Learning Paradigm,
CVPR23(7876-7885)
IEEE DOI
2309
BibRef
Zhang, Y.[Yong],
Pan, Y.W.[Ying-Wei],
Yao, T.[Ting],
Huang, R.[Rui],
Mei, T.[Tao],
Chen, C.W.[Chang-Wen],
Learning to Generate Language-Supervised and Open-Vocabulary Scene
Graph Using Pre-Trained Visual-Semantic Space,
CVPR23(2915-2924)
IEEE DOI
2309
BibRef
Kundu, S.[Sanjoy],
Aakur, S.N.[Sathyanarayanan N.],
IS-GGT: Iterative Scene Graph Generation with Generative Transformers,
CVPR23(6292-6301)
IEEE DOI
2309
BibRef
Jin, T.L.[Tian-Lei],
Guo, F.T.[Fang-Tai],
Meng, Q.W.[Qi-Wei],
Zhu, S.Q.[Shi-Qiang],
Xi, X.M.[Xiang-Ming],
Wang, W.[Wen],
Mu, Z.[Zonghao],
Song, W.[Wei],
Fast Contextual Scene Graph Generation with Unbiased Context
Augmentation,
CVPR23(6302-6311)
IEEE DOI
2309
BibRef
Feng, M.T.[Ming-Tao],
Hou, H.R.[Hao-Ran],
Zhang, L.[Liang],
Wu, Z.[Ziiie],
Guo, Y.L.[Yu-Lan],
Mian, A.[Ajmal],
3D Spatial Multimodal Knowledge Accumulation for Scene Graph
Prediction in Point Cloud,
CVPR23(9182-9191)
IEEE DOI
2309
BibRef
Jung, D.[Deunsol],
Kim, S.[Sanghyun],
Kim, W.H.[Won Hwa],
Cho, M.[Minsu],
Devil's on the Edges: Selective Quad Attention for Scene Graph
Generation,
CVPR23(18664-18674)
IEEE DOI
2309
BibRef
Zheng, C.F.[Chao-Fan],
Lyu, X.Y.[Xin-Yu],
Gao, L.L.[Lian-Li],
Dai, B.[Bo],
Song, J.K.[Jing-Kuan],
Prototype-Based Embedding Network for Scene Graph Generation,
CVPR23(22783-22792)
IEEE DOI
2309
BibRef
Qiu, Y.[Yue],
Sun, Y.J.[Yan-Jun],
Matsuzawa, F.[Fumiya],
Iwata, K.[Kenji],
Kataoka, H.[Hirokatsu],
Graph Representation for Order-aware Visual Transformation,
CVPR23(22793-22802)
IEEE DOI
2309
BibRef
Nag, S.[Sayak],
Min, K.[Kyle],
Tripathi, S.[Subarna],
Roy-Chowdhury, A.K.[Amit K.],
Unbiased Scene Graph Generation in Videos,
CVPR23(22803-22813)
IEEE DOI
2309
BibRef
Biswas, B.A.[Bashirul Azam],
Ji, Q.[Qiang],
Probabilistic Debiasing of Scene Graphs,
CVPR23(10429-10438)
IEEE DOI
2309
BibRef
Wang, Z.Q.[Zi-Qin],
Cheng, B.[Bowen],
Zhao, L.C.[Li-Chen],
Xu, D.[Dong],
Tang, Y.[Yang],
Sheng, L.[Lu],
VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic
Scene Graph Prediction in Point Cloud,
CVPR23(21560-21569)
IEEE DOI
2309
BibRef
Yang, B.N.[Bing-Nan],
Zhang, M.[Mi],
Zhang, Z.[Zhan],
Zhang, Z.[Zhili],
Hu, X.Y.[Xiang-Yun],
TopDiG: Class-Agnostic Topological Directional Graph Extraction from
Remote Sensing Images,
CVPR23(1265-1274)
IEEE DOI
2309
BibRef
Yang, J.K.[Jing-Kang],
Peng, W.X.[Wen-Xuan],
Li, X.T.[Xiang-Tai],
Guo, Z.[Zujin],
Chen, L.Y.[Liang-Yu],
Li, B.[Bo],
Ma, Z.[Zheng],
Zhou, K.Y.[Kai-Yang],
Zhang, W.[Wayne],
Loy, C.C.[Chen Change],
Liu, Z.W.[Zi-Wei],
Panoptic Video Scene Graph Generation,
CVPR23(18675-18685)
IEEE DOI
2309
BibRef
Zhang, R.N.[Ruo-Nan],
An, G.[Gaoyun],
Causal Property Based Anti-conflict Modeling with Hybrid Data
Augmentation for Unbiased Scene Graph Generation,
ACCV22(IV:571-587).
Springer DOI
2307
BibRef
Agarwal, R.[Rishi],
Chandra, T.S.[Tirupati Saketh],
Patil, V.[Vaidehi],
Mahapatra, A.[Aniruddha],
Kulkarni, K.[Kuldeep],
Vinay, V.[Vishwa],
GEMS: Scene Expansion using Generative Models of Graphs,
WACV23(157-166)
IEEE DOI
2302
Measurement, Visualization, Sequential analysis,
Computational modeling, Image retrieval, Genomics,
Vision + language and/or other modalities
BibRef
Feng, S.Y.[Sheng-Yu],
Mostafa, H.[Hesham],
Nassar, M.[Marcel],
Majumdar, S.[Somdeb],
Tripathi, S.[Subarna],
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs,
WACV23(5119-5128)
IEEE DOI
2302
Fluctuations, Source coding, Genomics, Benchmark testing,
Transformers, Bioinformatics, visual reasoning
BibRef
Adaimi, G.[George],
Mizrahi, D.[David],
Alahi, A.[Alexandre],
Composite Relationship Fields with Transformers for Scene Graph
Generation,
WACV23(52-64)
IEEE DOI
2302
Visualization, Image recognition, Image synthesis, Semantics,
Genomics, Transformers, Real-time systems,
Commercial/retail
BibRef
Hasegawa, S.[So],
Hiromoto, M.[Masayuki],
Nakagawa, A.[Akira],
Umeda, Y.[Yuhei],
Improving Predicate Representation in Scene Graph Generation by
Self-Supervised Learning,
WACV23(2739-2748)
IEEE DOI
2302
Visualization, Genomics, Self-supervised learning, Task analysis,
Bioinformatics,
and un-supervised learning)
BibRef
Trivedy, V.[Vivek],
Latecki, L.J.[Longin Jan],
CNN2Graph: Building Graphs for Image Classification,
WACV23(1-11)
IEEE DOI
2302
Training, Representation learning, Costs, Transformers,
Inference algorithms, Graph neural networks, Data models,
and un-supervised learning)
BibRef
Wang, J.J.[Jian-Jia],
Zhao, X.[Xin],
Wu, C.[Chong],
Hancock, E.R.[Edwin R.],
Inferring Edges from Weights in the Debye Model,
ICPR22(3845-3850)
IEEE DOI
2212
Gamma distribution, Solid modeling, Temperature distribution,
Thermodynamics, Temperature dependence, Solids, Probability distribution
BibRef
Li, J.[Jingci],
Lu, G.Q.[Guang-Quan],
Wu, Z.T.[Zheng-Tian],
Multi-View Graph Autoencoder for Unsupervised Graph Representation
Learning,
ICPR22(2213-2218)
IEEE DOI
2212
Representation learning, Training, Social networking (online),
Network topology, Aggregates, Topology
BibRef
Seymour, Z.[Zachary],
Mithun, N.C.[Niluthpol Chowdhury],
Chiu, H.P.[Han-Pang],
Samarasekera, S.[Supun],
Kumar, R.[Rakesh],
GraphMapper: Efficient Visual Navigation by Scene Graph Generation,
ICPR22(4146-4153)
IEEE DOI
2212
Visualization,
Simultaneous localization and mapping, Navigation, Autonomous agents
BibRef
Zhang, Y.Z.[Yi-Zhou],
Zheng, Z.H.[Zhao-Heng],
Nevatia, R.[Ram],
Liu, Y.[Yan],
Improving Weakly Supervised Scene Graph Parsing through Object
Grounding,
ICPR22(4058-4064)
IEEE DOI
2212
Measurement, Visualization, Grounding, Genomics,
Image representation, Graph neural networks
BibRef
Yamamoto, T.[Takuma],
Obinata, Y.Y.[Yu-Ya],
Nakayama, O.[Osafumi],
Transformer-based Scene Graph Generation Network With Relational
Attention Module,
ICPR22(2034-2041)
IEEE DOI
2212
Training, Adaptation models, Visualization, Annotations, Genomics,
Training data, Predictive models
BibRef
Kim, M.S.[Min-Sang],
Baek, S.[Seungjun],
ComDensE: Combined Dense Embedding of Relation-aware and Common
Features for Knowledge Graph Completion,
ICPR22(1989-1995)
IEEE DOI
2212
Computational modeling, Neural networks,
Feature extraction, Encoding, Natural language processing
BibRef
Yu, X.[Xiang],
Li, J.[Jie],
Yuan, S.J.[Shi-Jing],
Wang, C.[Chao],
Wu, C.T.[Chen-Tao],
Zero-Shot Scene Graph Generation with Relational Graph Neural
Networks,
ICPR22(1894-1900)
IEEE DOI
2212
Training, Measurement, Visualization, Correlation, Semantics, Genomics,
Feature extraction
BibRef
Shit, S.[Suprosanna],
Koner, R.[Rajat],
Wittmann, B.[Bastian],
Paetzold, J.[Johannes],
Ezhov, I.[Ivan],
Li, H.W.[Hong-Wei],
Pan, J.Z.[Jia-Zhen],
Sharifzadeh, S.[Sahand],
Kaissis, G.[Georgios],
Tresp, V.[Volker],
Menze, B.[Bjoern],
Relationformer: A Unified Framework for Image-to-Graph Generation,
ECCV22(XXXVII:422-439).
Springer DOI
2211
BibRef
Zhang, A.[Ao],
Yao, Y.[Yuan],
Chen, Q.Y.[Qian-Yu],
Ji, W.[Wei],
Liu, Z.Y.[Zhi-Yuan],
Sun, M.[Maosong],
Chua, T.S.[Tat-Seng],
Fine-Grained Scene Graph Generation with Data Transfer,
ECCV22(XXVII:409-424).
Springer DOI
2211
BibRef
Li, Y.S.[Yan-Sheng],
Wang, T.Z.[Ting-Zhu],
Wu, K.[Kang],
Wang, L.L.[Lin-Lin],
Guo, X.[Xin],
Wang, W.B.[Wen-Bin],
Fine-grained Scene Graph Generation via Sample-level Bias Prediction,
ECCV24(XXVI: 18-35).
Springer DOI
2412
BibRef
Deng, Y.M.[You-Ming],
Li, Y.S.[Yan-Sheng],
Zhang, Y.J.[Yong-Jun],
Xiang, X.[Xiang],
Wang, J.[Jian],
Chen, J.D.[Jing-Dong],
Ma, J.Y.[Jia-Yi],
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation,
ECCV22(XXVII:266-283).
Springer DOI
2211
BibRef
Yang, J.K.[Jing-Kang],
Ang, Y.Z.[Yi Zhe],
Guo, Z.[Zujin],
Zhou, K.Y.[Kai-Yang],
Zhang, W.[Wayne],
Liu, Z.W.[Zi-Wei],
Panoptic Scene Graph Generation,
ECCV22(XXVII:178-196).
Springer DOI
2211
BibRef
He, T.[Tao],
Gao, L.L.[Lian-Li],
Song, J.K.[Jing-Kuan],
Li, Y.F.[Yuan-Fang],
Towards Open-Vocabulary Scene Graph Generation with Prompt-Based
Finetuning,
ECCV22(XXVIII:56-73).
Springer DOI
2211
BibRef
Xu, L.[Li],
Qu, H.X.[Hao-Xuan],
Kuen, J.[Jason],
Gu, J.X.[Jiu-Xiang],
Liu, J.[Jun],
Meta Spatio-Temporal Debiasing for Video Scene Graph Generation,
ECCV22(XXVII:374-390).
Springer DOI
2211
BibRef
Li, W.[Wei],
Zhang, H.W.[Hai-Wei],
Bai, Q.J.[Qi-Jie],
Zhao, G.Q.[Guo-Qing],
Jiang, N.[Ning],
Yuan, X.J.[Xiao-Jie],
PPDL: Predicate Probability Distribution based Loss for Unbiased
Scene Graph Generation,
CVPR22(19425-19434)
IEEE DOI
2210
Training, Visualization, Analytical models, Computational modeling,
Semantics, Optimization methods, Tail, retrieval, Recognition: detection
BibRef
Teng, Y.[Yao],
Wang, L.M.[Li-Min],
Structured Sparse R-CNN for Direct Scene Graph Generation,
CVPR22(19415-19424)
IEEE DOI
2210
Training, Visualization, Head, Pipelines, Genomics, Detectors,
Object detection, Scene analysis and understanding,
retrieval
BibRef
Dong, X.N.[Xing-Ning],
Gan, T.[Tian],
Song, X.M.[Xue-Meng],
Wu, J.L.[Jian-Long],
Cheng, Y.[Yuan],
Nie, L.Q.[Li-Qiang],
Stacked Hybrid-Attention and Group Collaborative Learning for
Unbiased Scene Graph Generation,
CVPR22(19405-19414)
IEEE DOI
2210
Measurement, Visualization, Image analysis, Codes,
Computational modeling, Pipelines, Vision + X
BibRef
Li, Y.M.[Yi-Ming],
Yang, X.S.[Xiao-Shan],
Xu, C.S.[Chang-Sheng],
Dynamic Scene Graph Generation via Anticipatory Pre-training,
CVPR22(13864-13873)
IEEE DOI
2210
Visualization, Correlation, Triples (Data structure), Semantics,
Predictive models, Transformers, Data mining, Visual reasoning
BibRef
Nguyen, E.[Eric],
Bui, T.[Tu],
Swaminathan, V.[Viswanathan],
Collomosse, J.[John],
OSCAR-Net: Object-centric Scene Graph Attention for Image Attribution,
ICCV21(14479-14488)
IEEE DOI
2203
Visualization, Shape, Scalability, Fingerprint recognition,
Transformers, Search problems,
Scene analysis and understanding
BibRef
Yao, Y.[Yuan],
Zhang, A.[Ao],
Han, X.[Xu],
Li, M.D.[Meng-Di],
Weber, C.[Cornelius],
Liu, Z.Y.[Zhi-Yuan],
Wermter, S.[Stefan],
Sun, M.S.[Mao-Song],
Visual Distant Supervision for Scene Graph Generation,
ICCV21(15796-15806)
IEEE DOI
2203
Visualization, Computational modeling, Noise reduction,
Supervised learning, Image representation, Probabilistic logic,
Vision + language
BibRef
Knyazev, B.[Boris],
de Vries, H.[Harm],
Cangea, C.[Catalina],
Taylor, G.W.[Graham W.],
Courville, A.[Aaron],
Belilovsky, E.[Eugene],
Generative Compositional Augmentations for Scene Graph Prediction,
ICCV21(15807-15817)
IEEE DOI
2203
Measurement, Training, Visualization, Training data, Genomics,
Generative adversarial networks,
Visual reasoning and logical representation
BibRef
Guo, Y.Y.[Yu-Yu],
Gao, L.L.[Lian-Li],
Wang, X.H.[Xuan-Han],
Hu, Y.X.[Yu-Xuan],
Xu, X.[Xing],
Lu, X.[Xu],
Shen, H.T.[Heng Tao],
Song, J.K.[Jing-Kuan],
From General to Specific: Informative Scene Graph Generation via
Balance Adjustment,
ICCV21(16363-16372)
IEEE DOI
2203
Training, Visualization, Triples (Data structure), Roads, Semantics,
Power line communications, Layout,
Visual reasoning and logical representation
BibRef
Lu, Y.C.[Yi-Chao],
Rai, H.[Himanshu],
Chang, J.[Jason],
Knyazev, B.[Boris],
Yu, G.[Guangwei],
Shekhar, S.[Shashank],
Taylor, G.W.[Graham W.],
Volkovs, M.[Maksims],
Context-aware Scene Graph Generation with Seq2Seq Transformers,
ICCV21(15911-15921)
IEEE DOI
2203
Training, Measurement, Visualization, Computational modeling,
Training data, Predictive models,
Visual reasoning and logical representation
BibRef
Zhong, Y.[Yiwu],
Shi, J.[Jing],
Yang, J.W.[Jian-Wei],
Xu, C.L.[Chen-Liang],
Li, Y.[Yin],
Learning to Generate Scene Graph from Natural Language Supervision,
ICCV21(1803-1814)
IEEE DOI
2203
Training, Visualization, Image recognition, Natural languages,
Detectors, Predictive models, Transformers, Vision + language,
Scene analysis and understanding
BibRef
Lee, W.[Wonhee],
Kim, S.[Sungeun],
Kim, G.[Gunhee],
Contextual Label Transformation for Scene Graph Generation,
ICIP21(2533-2537)
IEEE DOI
2201
Visualization, Head, Annotations, Scalability, Image processing,
Object detection, Scene graph generation, label transformation
BibRef
Zhang, Z.C.[Zhi-Chao],
Dong, J.Y.[Jun-Yu],
Zhao, Q.[Qilu],
Qi, L.[Lin],
Zhang, S.[Shu],
Attention LSTM for Scene Graph Generation,
ICIVC21(264-268)
IEEE DOI
2112
Degradation, Deep learning, Visualization, Fuses, Message passing,
Semantics, Feature extraction, scene graph generation,
message passing
BibRef
Chen, H.[Hao],
Chen, L.[Lin],
Kuang, X.Y.[Xiao-Yun],
Xu, A.D.[Ai-Dong],
Yang, Y.W.[Yi-Wei],
A Safe and Intelligent Knowledge Graph Construction Model Suitable
for Smart Gridaper Title,
ICIVC21(253-258)
IEEE DOI
2112
Computational modeling, Smart grids, smart grid, knowledge map,
ternary extraction
BibRef
Yang, G.C.[Geng-Cong],
Zhang, J.Y.[Jing-Yi],
Zhang, Y.[Yong],
Wu, B.Y.[Bao-Yuan],
Yang, Y.[Yujiu],
Probabilistic Modeling of Semantic Ambiguity for Scene Graph
Generation,
CVPR21(12522-12531)
IEEE DOI
2111
Visualization, Uncertainty, Semantics, Diversity reception,
Measurement uncertainty, Predictive models, Linguistics
BibRef
Li, R.J.[Rong-Jie],
Zhang, S.Y.[Song-Yang],
Wan, B.[Bo],
He, X.M.[Xu-Ming],
Bipartite Graph Network with Adaptive Message Passing for Unbiased
Scene Graph Generation,
CVPR21(11104-11114)
IEEE DOI
2111
Training, Visualization, Adaptive systems,
Message passing, Neural networks, Genomics
BibRef
Liu, H.Y.[Heng-Yue],
Yan, N.[Ning],
Mortazavi, M.[Masood],
Bhanu, B.[Bir],
Fully Convolutional Scene Graph Generation,
CVPR21(11541-11551)
IEEE DOI
2111
Measurement, Visualization, Semantics, Pipelines, Genomics,
Object detection, Detectors
BibRef
Suhail, M.[Mohammed],
Mittal, A.[Abhay],
Siddiquie, B.[Behjat],
Broaddus, C.[Chris],
Eledath, J.[Jayan],
Medioni, G.[Gerard],
Sigal, L.[Leonid],
Energy-Based Learning for Scene Graph Generation,
CVPR21(13931-13940)
IEEE DOI
2111
Training, Visualization, Computational modeling,
Genomics, Benchmark testing
BibRef
Dhingra, N.[Naina],
Ritter, F.[Florian],
Kunz, A.[Andreas],
BGT-Net: Bidirectional GRU Transformer Network for Scene Graph
Generation,
WiCV21(2150-2159)
IEEE DOI
2109
Visualization, Image edge detection,
Genomics, Softening
BibRef
Liao, W.T.[Wen-Tong],
Lan, C.L.[Cui-Ling],
Yang, M.Y.[Michael Ying],
Zeng, W.J.[Wen-Jun],
Rosenhahn, B.[Bodo],
Target-Tailored Source-Transformation for Scene Graph Generation,
MULA21(1663-1671)
IEEE DOI
2109
Visualization, Message passing, Image edge detection, Semantics,
Genomics, Transforms, Object detection
BibRef
Wang, W.B.[Wen-Bin],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation,
ECCV20(XIII:222-239).
Springer DOI
2011
BibRef
Zareian, A.[Alireza],
Karaman, S.[Svebor],
Chang, S.F.[Shih-Fu],
Bridging Knowledge Graphs to Generate Scene Graphs,
ECCV20(XXIII:606-623).
Springer DOI
2011
BibRef
Tang, K.H.[Kai-Hua],
Niu, Y.L.[Yu-Lei],
Huang, J.Q.[Jian-Qiang],
Shi, J.X.[Jia-Xin],
Zhang, H.W.[Han-Wang],
Unbiased Scene Graph Generation from Biased Training,
CVPR20(3713-3722)
IEEE DOI
2008
Visualization, Training, Task analysis, Predictive models, Dogs,
Cognition, Genomics
BibRef
Kurosawa, I.[Ikuto],
Kobayashi, T.[Tetsunori],
Hayashi, Y.[Yoshihiko],
Exploring and Exploiting the Hierarchical Structure of a Scene for
Scene Graph Generation,
ICPR21(1422-1429)
IEEE DOI
2105
Visualization, Aggregates, Neural networks, Genomics,
Knowledge discovery, Labeling
BibRef
Lin, X.[Xin],
Ding, C.X.[Chang-Xing],
Zhan, Y.B.[Yi-Bing],
Li, Z.J.[Zi-Jian],
Tao, D.C.[Da-Cheng],
HL-Net: Heterophily Learning Network for Scene Graph Generation,
CVPR22(19454-19463)
IEEE DOI
2210
Visualization, Image analysis, Codes, Message passing, Genomics,
Transformers, Scene analysis and understanding,
Visual reasoning
BibRef
Lin, X.[Xin],
Ding, C.X.[Chang-Xing],
Zhang, J.[Jing],
Zhan, Y.B.[Yi-Bing],
Tao, D.C.[Da-Cheng],
RU-Net: Regularized Unrolling Network for Scene Graph Generation,
CVPR22(19435-19444)
IEEE DOI
2210
Measurement, Visualization, Systematics, Laplace equations,
Image analysis, Correlation, Databases,
Visual reasoning
BibRef
Lin, X.[Xin],
Ding, C.X.[Chang-Xing],
Zeng, J.Q.[Jin-Quan],
Tao, D.C.[Da-Cheng],
GPS-Net: Graph Property Sensing Network for Scene Graph Generation,
CVPR20(3743-3752)
IEEE DOI
2008
Context modeling, Mathematical model, Ear, Visualization,
Message passing, Dogs, Legged locomotion
BibRef
Zareian, A.[Alireza],
Wang, Z.C.[Zhe-Can],
You, H.X.[Hao-Xuan],
Chang, S.F.[Shih-Fu],
Learning Visual Commonsense for Robust Scene Graph Generation,
ECCV20(XXIII:642-657).
Springer DOI
2011
BibRef
Chen, L.,
Zhang, H.,
Xiao, J.,
He, X.,
Pu, S.,
Chang, S.,
Counterfactual Critic Multi-Agent Training for Scene Graph Generation,
ICCV19(4612-4622)
IEEE DOI
2004
biology computing, entropy, genomics, gradient methods, graph theory,
image processing, learning (artificial intelligence),
BibRef
Gkanatsios, N.,
Pitsikalis, V.,
Koutras, P.,
Maragos, P.,
Attention-Translation-Relation Network for Scalable Scene Graph
Generation,
SGRL19(1754-1764)
IEEE DOI
2004
computer graphics, feature extraction,
attention-translation-relation network, background class,
Vision and Language
BibRef
Chen, Z.W.[Zhan-Wen],
Rezayi, S.[Saed],
Li, S.[Sheng],
More Knowledge, Less Bias: Unbiasing Scene Graph Generation with
Explicit Ontological Adjustment,
WACV23(4012-4021)
IEEE DOI
2302
Training, Visualization, Solid modeling, Source coding,
Image edge detection, Semantics, Knowledge based systems,
Vision + language and/or other modalities
BibRef
Gu, J.X.[Jiu-Xiang],
Zhao, H.D.[Han-Dong],
Lin, Z.[Zhe],
Li, S.[Sheng],
Cai, J.F.[Jian-Fei],
Ling, M.Y.[Ming-Yang],
Scene Graph Generation With External Knowledge and Image Reconstruction,
CVPR19(1969-1978).
IEEE DOI
2002
BibRef
Wang, W.B.[Wen-Bin],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Exploring Context and Visual Pattern of Relationship for Scene Graph
Generation,
CVPR19(8180-8189).
IEEE DOI
2002
BibRef
Khademi, M.[Mahmoud],
Schulte, O.[Oliver],
Dynamic Gated Graph Neural Networks for Scene Graph Generation,
ACCV18(VI:669-685).
Springer DOI
1906
BibRef
Li, Y.K.[Yi-Kang],
Ouyang, W.L.[Wan-Li],
Zhou, B.[Bolei],
Shi, J.P.[Jian-Ping],
Zhang, C.[Chao],
Wang, X.G.[Xiao-Gang],
Factorizable Net: An Efficient Subgraph-Based Framework for Scene Graph
Generation,
ECCV18(I: 346-363).
Springer DOI
1810
BibRef
Yang, J.W.[Jian-Wei],
Lu, J.[Jiasen],
Lee, S.[Stefan],
Batra, D.[Dhruv],
Parikh, D.[Devi],
Graph R-CNN for Scene Graph Generation,
ECCV18(I: 690-706).
Springer DOI
1810
BibRef
Xu, D.,
Zhu, Y.,
Choy, C.B.,
Fei-Fei, L.[Li],
Scene Graph Generation by Iterative Message Passing,
CVPR17(3097-3106)
IEEE DOI
1711
Image edge detection, Message passing, Predictive models,
Proposals, Semantics, Visualization
BibRef
Li, Y.,
Ouyang, W.,
Zhou, B.,
Wang, K.,
Wang, X.,
Scene Graph Generation from Objects, Phrases and Region Captions,
ICCV17(1270-1279)
IEEE DOI
1802
graph theory, image classification, image representation,
neural nets, object detection,
Visualization
BibRef
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Network Embedding, Graph Embedding .