13.3.3 Scene Graph Construction, Scene Graph Generation

Chapter Contents (Back)
Graph Structure. Graph Generation. Graph Construction. Scene Graph. Object Recognition.

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.[Runtong],
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, Pattern recognition, Proposals, Visual reasoning 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


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

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

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

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

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, Pattern recognition, Mutual information, Self- semi- meta- unsupervised learning 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, Pattern recognition 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, Pattern recognition, 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 .


Last update:Apr 10, 2024 at 09:54:40