7.1.7.6 Object Localization

Chapter Contents (Back)
Object Localization. Localization.
See also Instance Segmentation.
See also Dense Object Detection.

Caucci, L.[Luca], Barrett, H.H.[Harrison H.], Devaney, N.[Nicholas], Rodríguez, J.J.[Jeffrey J.],
Application of the Hotelling and ideal observers to detection and localization of exoplanets,
JOSA-A(24), No. 12, December 2007, pp. B13-B24.
WWW Link. 0801
Object detection. Planets. BibRef

Gao, D.S.[Da-Shan], Han, S.H.[Sun-Hyoung], Vasconcelos, N.M.[Nuno M.],
Discriminant Saliency, the Detection of Suspicious Coincidences, and Applications to Visual Recognition,
PAMI(31), No. 6, June 2009, pp. 989-1005.
IEEE DOI 0904
BibRef
Earlier: A1, A3, Only:
Bottom-up saliency is a discriminant process,
ICCV07(1-6).
IEEE DOI 0710
BibRef
Earlier: A1, A3, Only:
Discriminant Interest Points are Stable,
CVPR07(1-6).
IEEE DOI 0706
Related to infomax, inference by detection of suspicious coincidences, classification with minimal uncertainty, and classification with minimum probability of error. Apply to localize objects in clutter. BibRef

Han, S.H.[Sun-Hyoung], Vasconcelos, N.M.[Nuno M.],
Complex discriminant features for object classification,
ICIP08(1700-1703).
IEEE DOI 0810
BibRef

Lampert, C.H.[Christoph H.], Blaschko, M.B.[Matthew B.], Hofmann, T.[Thomas],
Efficient Subwindow Search: A Branch and Bound Framework for Object Localization,
PAMI(31), No. 12, December 2009, pp. 2129-2142.
IEEE DOI 0911
BibRef
Earlier:
Beyond sliding windows: Object localization by efficient subwindow search,
CVPR08(1-8).
IEEE DOI 0806
Award, CVPR. Efficient search for existence of object. BibRef

Blaschko, M.B.[Matthew B.],
Branch and Bound Strategies for Non-maximal Suppression in Object Detection,
EMMCVPR11(385-398).
Springer DOI 1107
BibRef

Lampert, C.H.[Christoph H.],
An efficient divide-and-conquer cascade for nonlinear object detection,
CVPR10(1022-1029).
IEEE DOI 1006
BibRef
Earlier:
Detecting objects in large image collections and videos by efficient subimage retrieval,
ICCV09(987-994).
IEEE DOI 0909
BibRef

Blaschko, M.B.[Matthew B.], Lampert, C.H.[Christoph H.],
Object Localization with Global and Local Context Kernels,
BMVC09(xx-yy).
PDF File. 0909
BibRef
Earlier:
Learning to Localize Objects with Structured Output Regression,
ECCV08(I: 2-15).
Springer DOI 0810
BibRef

Shi, Z.Y.[Zhi-Yuan], Hospedales, T.M.[Timothy M.], Xiang, T.[Tao],
Bayesian Joint Modelling for Object Localisation in Weakly Labelled Images,
PAMI(37), No. 10, October 2015, pp. 1959-1972.
IEEE DOI 1509
BibRef
Earlier:
Bayesian Joint Topic Modelling for Weakly Supervised Object Localisation,
ICCV13(2984-2991)
IEEE DOI 1403
Bayesian; Joint Topic Modelling; Weakly Supervised Adaptation models BibRef

Shi, Z.Y.[Zhi-Yuan], Yang, Y.X.[Yong-Xin], Hospedales, T.M.[Timothy M.], Xiang, T.[Tao],
Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes,
PAMI(39), No. 12, December 2017, pp. 2525-2538.
IEEE DOI 1711
BibRef
Earlier:
Weakly Supervised Learning of Objects, Attributes and Their Associations,
ECCV14(II: 472-487).
Springer DOI 1408
Correlation, Detectors, Semantics, Indian buffet process, Weakly supervised learning, non-parametric Bayesian model. Finding bounding box. BibRef

Halawani, A.[Alaa], Li, H.B.[Hai-Bo],
100 lines of code for shape-based object localization,
PR(60), No. 1, 2016, pp. 458-472.
Elsevier DOI 1609
Code, Object Detection. Object detection BibRef

Wang, L.T.[Lian-Tao], Lu, J.F.[Jian-Feng], Li, X.Y.[Xiang-Yu], Huan, Z.[Zhan], Liang, J.Z.[Jiu-Zhen], Chen, S.Y.[Shu-Yue],
Learning arbitrary-shape object detector from bounding-box annotation by searching region-graph,
PRL(87), No. 1, 2017, pp. 171-176.
Elsevier DOI 1703
Object localization BibRef

Feng, Y.J.[You-Ji], Wu, Y.H.[Yi-Hong], Fan, L.X.[Li-Xin],
Real-time SLAM relocalization with online learning of binary feature indexing,
MVA(28), No. 8, November 2017, pp. 953-963.
WWW Link. 1710
BibRef
Earlier:
Online Learning of Binary Feature Indexing for Real-Time SLAM Relocalization,
BD3DCV14(206-217).
Springer DOI 1504
BibRef

Wu, S.K.[Sheng-Kai], Li, X.P.[Xiao-Ping], Wang, X.G.[Xing-Gang],
IoU-aware single-stage object detector for accurate localization,
IVC(97), 2020, pp. 103911.
Elsevier DOI 2005
IoU prediction, IoU-aware detector, Accurate localization, Single-stage object detector BibRef

Chen, Q.A.[Qi-Ang], Wang, P.S.[Pei-Song], Cheng, A.[Anda], Wang, W.[Wanguo], Zhang, Y.F.[Yi-Fan], Cheng, J.[Jian],
Robust one-stage object detection with location-aware classifiers,
PR(105), 2020, pp. 107334.
Elsevier DOI 2006
Object detetion, Classification, Localization, Feature visualization, Receptive field BibRef

Wang, B.S.[Bi-Sheng], Cao, G.[Guo], Zhou, L.[Licun], Zhang, Y.Q.[You-Qiang], Shang, Y.F.[Yan-Feng],
Task differentiation: Constructing robust branches for precise object detection,
CVIU(199), 2020, pp. 103030.
Elsevier DOI 2009
Separate localization and classification components. Task differentiation, Feature fusion, Object detection, SSD BibRef

Gou, L.J.[Li-Jun], Wu, S.K.[Sheng-Kai], Yang, J.R.[Jin-Rong], Yu, H.C.[Hang-Cheng], Li, X.P.[Xiao-Ping],
Gaussian guided IoU: A better metric for balanced learning on object detection,
IET-CV(16), No. 6, 2022, pp. 556-566.
DOI Link 2208
BibRef

Hu, Y.Z.[Yan-Zhu], Zhu, D.D.[Dong-Dong], Ai, X.B.[Xin-Bo], Xu, Y.[Yabo],
Category-wise feature extractor based on ADL method for weak-supervised object localisation,
IET-IPR(14), No. 15, 15 December 2020, pp. 3965-3974.
DOI Link 2103
BibRef

Peng, H.Y.[Han-Yang], Yu, S.Q.[Shi-Qi],
A Systematic IoU-Related Method: Beyond Simplified Regression for Better Localization,
IP(30), 2021, pp. 5032-5044.
IEEE DOI 2106
Standards, Detectors, Location awareness, Computer architecture, Measurement, Systematics, Object detection, Object detection, optimization BibRef

Wang, B.[Bo], Yuan, C.F.[Chun-Feng], Li, B.[Bing], Ding, X.M.[Xin-Miao], Li, Z.Y.[Ze-Ya], Wu, Y.[Ying], Hu, W.M.[Wei-Ming],
Multi-Scale Low-Discriminative Feature Reactivation for Weakly Supervised Object Localization,
IP(30), 2021, pp. 6050-6065.
IEEE DOI 2107
Location awareness, Neurons, Task analysis, Pattern recognition, Automation, Search problems, Proposals, multi-scale class activation mapping BibRef

Yang, L.[Li], Xu, Y.[Yan], Wang, S.[Shaoru], Yuan, C.F.[Chun-Feng], Zhang, Z.Q.[Zi-Qi], Li, B.[Bing], Hu, W.M.[Wei-Ming],
PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling,
IP(31), 2022, pp. 5121-5133.
IEEE DOI 2208
Location awareness, Detectors, Feature extraction, Semantics, Proposals, Head, Pattern recognition, Object detection, convolutional neural network BibRef

Benassou, S.N.[Sabrina Narimene], Shi, W.Z.[Wu-Zhen], Jiang, F.[Feng], Benzine, A.[Abdallah],
Hierarchical complementary learning for weakly supervised object localization,
SP:IC(100), 2022, pp. 116520.
Elsevier DOI 2112
Weakly supervised object localization, Class activation map, Complementary map, Fusion strategy BibRef

Wang, X.L.[Xiao-Lian], Hu, X.[Xiyuan], Chen, C.[Chen], Peng, S.[Silong],
Regularizing deep networks with label geometry for accurate object localization on small training datasets,
PRL(154), 2022, pp. 53-59.
Elsevier DOI 2202
Object detection, Object localization, Label geometry, Box evolution, Small dataset, Human-machine interaction BibRef

Piao, Z.Q.[Zheng-Quan], Wang, J.[Junbo], Tang, L.[Linbo], Zhao, B.J.[Bao-Jun], Wang, W.Z.[Wen-Zheng],
AccLoc: Anchor-Free and two-stage detector for accurate object localization,
PR(126), 2022, pp. 108523.
Elsevier DOI 2204
Object detection, Accurate localization, Anchor-free, NMS-free, Two-stage BibRef

Santiago, C.[Carlos], Medley, D.O.[Daniela O.], Marques, J.S.[Jorge S.], Nascimento, J.C.[Jacinto C.],
Model-Agnostic Temporal Regularizer for Object Localization Using Motion Fields,
IP(31), 2022, pp. 2478-2487.
IEEE DOI 2204
Location awareness, Tracking, Trajectory, Predictive models, Computational modeling, Estimation, Motion segmentation, temporal regularization BibRef

Panwar, K.[Kuntal], Babu, P.[Prabhu], Stoica, P.[Petre],
Maximum Likelihood Algorithm for Time-Delay Based Multistatic Target Localization,
SPLetters(29), 2022, pp. 847-851.
IEEE DOI 2204
Location awareness, Signal processing algorithms, Receivers, Noise measurement, Maximum likelihood estimation, Transmitters, majorization-minimization BibRef

Hui, W.J.[Wen-Jun], Tan, C.C.[Chuang-Chuang], Gu, G.H.[Guang-Hua], Zhao, Y.[Yao],
Gradient-based refined class activation map for weakly supervised object localization,
PR(128), 2022, pp. 108664.
Elsevier DOI 2205
Weakly supervised object localization, Gradients of loss function, Class-specific mask, Category consistency BibRef

Zhang, D.W.[Ding-Wen], Han, J.W.[Jun-Wei], Cheng, G.[Gong], Yang, M.H.[Ming-Hsuan],
Weakly Supervised Object Localization and Detection: A Survey,
PAMI(44), No. 9, September 2022, pp. 5866-5885.
IEEE DOI 2208
Location awareness, Annotations, Training, Task analysis, Detectors, Supervised learning, Weakly supervised learning, object detection BibRef

Xie, X.X.[Xing-Xing], Lang, C.B.[Chun-Bo], Miao, S.C.[Shi-Cheng], Cheng, G.[Gong], Li, K.[Ke], Han, J.W.[Jun-Wei],
Mutual-Assistance Learning for Object Detection,
PAMI(45), No. 12, December 2023, pp. 15171-15184.
IEEE DOI 2311
BibRef

Wang, D.[Dong], Shang, K.[Kun], Wu, H.[Huaming], Wang, C.[Ce],
Decoupled R-CNN: Sensitivity-Specific Detector for Higher Accurate Localization,
CirSysVideo(32), No. 9, September 2022, pp. 6324-6336.
IEEE DOI 2209
Proposals, Detectors, Task analysis, Sensitivity, Object detection, Training, Feature extraction, Object detection, R-CNN, decoupled R-CNN BibRef

Xie, N.[Ningbo], Ouyang, S.[Shan], Liao, K.[Kefei], Wang, H.T.[Hai-Tao], Jiang, J.Z.[Jun-Zheng],
Near-Field Multiple Target Localization in Frequency Diverse Array Based on Tensor Decomposition,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Meng, M.[Meng], Zhang, T.Z.[Tian-Zhu], Zhang, Z.[Zhe], Zhang, Y.D.[Yong-Dong], Wu, F.[Feng],
Adversarial Transformers for Weakly Supervised Object Localization,
IP(31), 2022, pp. 7130-7143.
IEEE DOI 2212
Location awareness, Transformers, Training, Robustness, Task analysis, Prototypes, Perturbation methods, weakly supervised object localization BibRef

Meng, M.[Meng], Zhang, T.Z.[Tian-Zhu], Zhang, Z.[Zhe], Zhang, Y.D.[Yong-Dong], Wu, F.[Feng],
Task-Aware Weakly Supervised Object Localization With Transformer,
PAMI(45), No. 7, July 2023, pp. 9109-9121.
IEEE DOI 2306
Location awareness, Task analysis, Transformers, Decoding, Prototypes, Training, Weakly supervised object localization, transformer BibRef

Choe, J.[Junsuk], Oh, S.J.[Seong Joon], Chun, S.[Sanghyuk], Lee, S.[Seungho], Akata, Z.[Zeynep], Shim, H.J.[Hyun-Jung],
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets,
PAMI(45), No. 2, February 2023, pp. 1732-1748.
IEEE DOI 2301
Location awareness, Task analysis, Training, Protocols, Measurement, Predictive models, Benchmark testing, Benchmark, dataset, evaluation, weakly supervised object localization BibRef

Koo, B.[Bongyeong], Choi, H.S.[Han-Soo], Kang, M.[Myungjoo],
Aggregation of attention and erasing for weakly supervised object localization,
IVC(129), 2023, pp. 104598.
Elsevier DOI 2301
Convolutional neural network, Weakly supervised learning, Object localization BibRef

Zhang, C.L.[Chen-Lin], Li, Y.[Yin], Wu, J.X.[Jian-Xin],
Weakly Supervised Foreground Learning for Weakly Supervised Localization and Detection,
PR(137), 2023, pp. 109279.
Elsevier DOI 2302
Weakly supervised object localization, Weakly supervised object detection, Foreground learning BibRef

Sui, L.[Lin], Zhang, C.L.[Chen-Lin], Wu, J.X.[Jian-Xin],
Salvage of Supervision in Weakly Supervised Object Detection and Segmentation,
PAMI(45), No. 8, August 2023, pp. 10394-10408.
IEEE DOI 2307
BibRef
Earlier:
Salvage of Supervision in Weakly Supervised Object Detection,
CVPR22(14207-14216)
IEEE DOI 2210
Object detection, Task analysis, Training, Annotations, Proposals, Detectors, Semantic segmentation, weakly supervised instance segmentation. Bridges, Visualization, Noise measurement, Recognition: detection, Self- semi- meta- Vision applications and systems BibRef

Liu, C.[Chang], Xie, S.R.[Shao-Rong], Li, X.M.[Xiao-Mao], Gao, J.T.[Jian-Tao], Xiao, W.P.[Wei-Ping], Fan, B.[Baojie], Peng, Y.[Yan],
Mitigate the classification ambiguity via localization-classification sequence in object detection,
PR(138), 2023, pp. 109418.
Elsevier DOI 2303
Object detection, Classification ambiguity, Refinement-aware classification BibRef

Qiu, H.Q.[He-Qian], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Cui, J.H.[Jian-Hua], Song, Z.C.[Zi-Chen], Wang, L.X.[Lan-Xiao], Zhang, M.J.[Min-Jian],
CrossDet++: Growing Crossline Representation for Object Detection,
CirSysVideo(33), No. 3, March 2023, pp. 1093-1108.
IEEE DOI 2303
Feature extraction, Semantics, Object detection, Proposals, Detectors, Training, Optimization, Object detection, semantic richness BibRef

Hwang, D.[Dongjun], Ha, J.W.[Jung-Woo], Shim, H.J.[Hyun-Jung], Choe, J.[Junsuk],
Entropy regularization for weakly supervised object localization,
PRL(169), 2023, pp. 1-7.
Elsevier DOI 2305
Deep learning, Weakly-supervised learning, Object localization, Entropy regularization, Dense attention map BibRef

Wang, L.[Lu], Fang, S.L.[Shi-Liang], Yang, Y.X.[Yi-Xin], Liu, X.H.[Xiong-Hou], Wang, M.Y.[Meng-Yuan],
A Feature-Level Fusion-Based Target Localization Method with the Hough Transform for Spatial Feature Extraction,
RS(15), No. 8, 2023, pp. 2121.
DOI Link 2305
BibRef

Shieh, J.L.[Jeng-Lun], Yu, S.F.[Sheng-Feng], Ruan, S.J.[Shanq-Jang],
Positive-weighting feature enhancement for weakly supervised object localization,
PRL(170), 2023, pp. 56-63.
Elsevier DOI 2306
Weakly-supervised learning, Object detection and localization, Class activation map, Feature enhancement BibRef

Li, Y.W.[Yuan-Wei], Zhu, E.[En], Chen, H.[Hang], Tan, J.Y.[Ji-Yong], Shen, L.[Li],
Dense Crosstalk Feature Aggregation for Classification and Localization in Object Detection,
CirSysVideo(33), No. 6, June 2023, pp. 2683-2695.
IEEE DOI 2306
Location awareness, Task analysis, Crosstalk, Feature extraction, Detectors, Multitasking, Object detection, Object detection, feature fusion BibRef

Zheng, Z.H.[Zhao-Hui], Ye, R.G.[Rong-Guang], Hou, Q.B.[Qi-Bin], Ren, D.W.[Dong-Wei], Wang, P.[Ping], Zuo, W.M.[Wang-Meng], Cheng, M.M.[Ming-Ming],
Localization Distillation for Object Detection,
PAMI(45), No. 8, August 2023, pp. 10070-10083.
IEEE DOI 2307
Location awareness, Object detection, Feature extraction, Detectors, Training, Head, Knowledge engineering, rotated object detection BibRef

Giuliari, F.[Francesco], Skenderi, G.[Geri], Cristani, M.[Marco], del Bue, A.[Alessio], Wang, Y.M.[Yi-Ming],
Leveraging Commonsense for Object Localisation in Partial Scenes,
PAMI(45), No. 10, October 2023, pp. 12038-12049.
IEEE DOI 2310
BibRef
Earlier: A1, A2, A3, A5, A4:
Spatial Commonsense Graph for Object Localisation in Partial Scenes,
CVPR22(19496-19505)
IEEE DOI 2210
Codes, Urban areas, Benchmark testing, Graph neural networks, Pattern recognition, Scene analysis and understanding, Vision + X BibRef

Zhu, L.[Lei], She, Q.[Qi], Chen, Q.[Qian], Meng, X.X.[Xiang-Xi], Geng, M.[Mufeng], Jin, L.[Lujia], Zhang, Y.B.[Yi-Bao], Ren, Q.S.[Qiu-Shi], Lu, Y.[Yanye],
Background-Aware Classification Activation Map for Weakly Supervised Object Localization,
PAMI(45), No. 12, December 2023, pp. 14175-14191.
IEEE DOI 2311
BibRef

Zhu, L.[Lei], Chen, Q.[Qian], Jin, L.[Lujia], You, Y.F.[Yun-Fei], Lu, Y.[Yanye],
Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization,
ECCV22(X:176-192).
Springer DOI 2211
BibRef

Tan, C.[Chuangchuang], Gu, G.H.[Guang-Hua], Ruan, T.[Tao], Wei, S.[Shikui], Zhao, Y.[Yao],
Dual-Gradients Localization Framework With Skip-Layer Connections for Weakly Supervised Object Localization,
MultMed(25), 2023, pp. 4933-4942.
IEEE DOI 2311
BibRef

Chen, D.[Dong], Pan, X.[Xingjia], Tang, F.[Fan], Dong, W.M.[Wei-Ming], Xu, C.S.[Chang-Sheng],
SPA2Net: Structure-Preserved Attention Activated Network for Weakly Supervised Object Localization,
IP(32), 2023, pp. 5779-5793.
IEEE DOI Code:
WWW Link. 2311
BibRef


Aiger, D.[Dror], Araujo, A.[André], Lynen, S.[Simon],
Yes, we CANN: Constrained Approximate Nearest Neighbors for local feature-based visual localization,
ICCV23(13293-13303)
IEEE DOI 2401
BibRef

Pu, Y.F.[Yi-Fan], Wang, Y.[Yiru], Xia, Z.[Zhuofan], Han, Y.Z.[Yi-Zeng], Wang, Y.L.[Yu-Lin], Gan, W.H.[Wei-Hao], Wang, Z.D.[Zi-Dong], Song, S.[Shiji], Huang, G.[Gao],
Adaptive Rotated Convolution for Rotated Object Detection,
ICCV23(6566-6577)
IEEE DOI Code:
WWW Link. 2401
BibRef

Rambhatla, S.S.[Sai Saketh], Misra, I.[Ishan], Chellappa, R.[Rama], Shrivastava, A.[Abhinav],
MOST: Multiple Object localization with Self-supervised Transformers for object discovery,
ICCV23(15777-15788)
IEEE DOI 2401
BibRef

Chen, Z.W.[Zhi-Wei], Ding, J.[Jinren], Cao, L.J.[Liu-Juan], Shen, Y.[Yunhang], Zhang, S.[Shengchuan], Jiang, G.[Guannan], Ji, R.R.[Rong-Rong],
Category-aware Allocation Transformer for Weakly Supervised Object Localization,
ICCV23(6620-6629)
IEEE DOI 2401
BibRef

Wu, P.Y.[Ping-Yu], Zhai, W.[Wei], Cao, Y.[Yang], Luo, J.B.[Jie-Bo], Zha, Z.J.[Zheng-Jun],
Spatial-Aware Token for Weakly Supervised Object Localization,
ICCV23(1844-1854)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhao, Y.Z.[Yu-Zhong], Ye, Q.X.[Qi-Xiang], Wu, W.J.[Wei-Jia], Shen, C.H.[Chun-Hua], Wan, F.[Fang],
Generative Prompt Model for Weakly Supervised Object Localization,
ICCV23(6328-6338)
IEEE DOI Code:
WWW Link. 2401
BibRef

Song, Y.[Yeonghwan], Jang, S.[Seokwoo], Katabi, D.[Dina], Son, J.[Jeany],
Unsupervised Object Localization with Representer Point Selection,
ICCV23(6511-6521)
IEEE DOI Code:
WWW Link. 2401
BibRef

García-Ruiz, P.[Pablo], Muñoz-Salinas, R.[Rafael], Medina-Carnicer, R.[Rafael], Marín-Jiménez, M.J.[Manuel J.],
Object Localization with Multiplanar Fiducial Markers: Accurate Pose Estimation,
IbPRIA23(454-465).
Springer DOI 2307
BibRef

Lee, Y.[Youngwan], Hwang, J.W.[Joong-Won], Kim, H.I.[Hyung-Il], Yun, K.[Kimin], Kwon, Y.J.[Yong-Jin], Bae, Y.[Yuseok], Hwang, S.J.[Sung Ju],
Localization Uncertainty Estimation for Anchor-free Object Detection,
Uncertainty22(27-42).
Springer DOI 2304
BibRef

Wang, L.X.[Lian-Xing], Li, H.X.[Hua-Xiong],
Weakly Supervised Object Localization Using Long-Range Semantic Foreground Activation,
ICPR22(4580-4586)
IEEE DOI 2212
Location awareness, Visualization, Correlation, Semantics, Benchmark testing, Transformers BibRef

Ueda, I.[Itsuki], Fukuhara, Y.[Yoshihiro], Kataoka, H.[Hirokatsu], Aizawa, H.[Hiroaki], Shishido, H.[Hidehiko], Kitahara, I.[Itaru],
Neural Density-Distance Fields,
ECCV22(XXXII:53-68).
Springer DOI 2211

WWW Link. BibRef

Bai, H.T.[Hao-Tian], Zhang, R.[Ruimao], Wang, J.[Jiong], Wan, X.[Xiang],
Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibration,
ECCV22(IX:612-628).
Springer DOI 2211
BibRef

Tseng, Y.Y.[Yu-Yun], Bell, A.[Alexander], Gurari, D.[Danna],
VizWiz-FewShot: Locating Objects in Images Taken by People with Visual Impairments,
ECCV22(VIII:575-591).
Springer DOI 2211
BibRef

Strafforello, O.[Ombretta], Rajasekart, V.[Vanathi], Kayhan, O.S.[Osman S.], Inel, O.[Oana], van Gemert, J.[Jan],
Humans Disagree With the IoU for Measuring Object Detector Localization Error,
ICIP22(1261-1265)
IEEE DOI 2211
Location awareness, Measurement uncertainty, Detectors, object detection, IoU, human preference BibRef

Wei, J.[Jun], Wang, S.[Sheng], Zhou, S.K.[S. Kevin], Cui, S.G.[Shu-Guang], Li, Z.[Zhen],
Weakly Supervised Object Localization Through Inter-class Feature Similarity and Intra-class Appearance Consistency,
ECCV22(XXX:195-210).
Springer DOI 2211
BibRef

Cole, E.[Elijah], Wilber, K.[Kimberly], Horn, G.V.[Grant Van], Yang, X.[Xuan], Fornoni, M.[Marco], Perona, P.[Pietro], Belongie, S.[Serge], Howard, A.[Andrew], Aodha, O.M.[Oisin Mac],
On Label Granularity and Object Localization,
ECCV22(X:604-620).
Springer DOI 2211
BibRef

Kim, E.[Eunji], Kim, S.[Siwon], Lee, J.[Jungbeom], Kim, H.W.[Hyun-Woo], Yoon, S.[Sungroh],
Bridging the Gap between Classification and Localization for Weakly Supervised Object Localization,
CVPR22(14238-14247)
IEEE DOI 2210
Location awareness, Bridges, Benchmark testing, Pattern recognition, Object recognition, Recognition: detection, Vision applications and systems BibRef

Xu, J.[Jilan], Hou, J.L.[Jun-Lin], Zhang, Y.J.[Yue-Jie], Feng, R.[Rui], Zhao, R.W.[Rui-Wei], Zhang, T.[Tao], Lu, X.Q.[Xue-Quan], Gao, S.[Shang],
CREAM: Weakly Supervised Object Localization via Class RE-Activation Mapping,
CVPR22(9427-9436)
IEEE DOI 2210
Location awareness, Training, Parameter estimation, Codes, Clustering algorithms, Benchmark testing, Recognition: detection, retrieval BibRef

Yu, X.H.[Xue-Hui], Chen, P.F.[Peng-Fei], Wu, D.[Di], Hassan, N.[Najmul], Li, G.R.[Guo-Rong], Yan, J.C.[Jun-Chi], Shi, H.[Humphrey], Ye, Q.X.[Qi-Xiang], Han, Z.J.[Zhen-Jun],
Object Localization under Single Coarse Point Supervision,
CVPR22(4858-4867)
IEEE DOI 2210
Location awareness, Training, Codes, Annotations, Semantics, Sensors, Recognition: detection, categorization, retrieval, Self- semi- meta- unsupervised learning BibRef

Zhu, L.[Lei], She, Q.[Qi], Chen, Q.[Qian], You, Y.F.[Yun-Fei], Wang, B.[Boyu], Lu, Y.[Yanye],
Weakly Supervised Object Localization as Domain Adaption,
CVPR22(14617-14626)
IEEE DOI 2210
Location awareness, Adaptation models, Codes, Shape, Pipelines, Benchmark testing, Self- semi- meta- Recognition: detection, Transfer/low-shot/long-tail learning BibRef

Gupta, S.[Saurav], Lakhotia, S.[Sourav], Rawat, A.[Abhay], Tallamraju, R.[Rahul],
ViTOL: Vision Transformer for Weakly Supervised Object Localization,
L3D-IVU22(4100-4109)
IEEE DOI 2210
Location awareness, Measurement, Visualization, Shape, Semantics, Computer architecture, Transformers BibRef

Feng, C.J.[Cheng-Jian], Zhong, Y.J.[Yu-Jie], Gao, Y.[Yu], Scott, M.R.[Matthew R.], Huang, W.L.[Wei-Lin],
TOOD: Task-aligned One-stage Object Detection,
ICCV21(3490-3499)
IEEE DOI 2203
Location awareness, Training, Measurement, Codes, Object detection, Detectors, Detection and localization in 2D and 3D, BibRef

Kim, J.[Jeesoo], Choe, J.[Junsuk], Yun, S.[Sangdoo], Kwak, N.[Nojun],
Normalization Matters in Weakly Supervised Object Localization,
ICCV21(3407-3416)
IEEE DOI 2203
Location awareness, Training, Annotations, Computer architecture, Performance gain, Solids, Efficient training and inference methods BibRef

Hu, Y.C.T.[Yu-Chih-Tuan], Chen, J.C.[Jun-Cheng], Kung, B.H.[Bo-Han], Hua, K.L.[Kai-Lung], Tan, D.S.[Daniel Stanley],
Naturalistic Physical Adversarial Patch for Object Detectors,
ICCV21(7828-7837)
IEEE DOI 2203
Manifolds, Image synthesis, Computational modeling, Detectors, Generative adversarial networks, Quality assessment, Detection and localization in 2D and 3D BibRef

Kalra, A.[Agastya], Stoppi, G.[Guy], Brown, B.[Bradley], Agarwal, R.[Rishav], Kadambi, A.[Achuta],
Towards Rotation Invariance in Object Detection,
ICCV21(3510-3520)
IEEE DOI 2203
Adaptation models, Uncertainty, Codes, Shape, Computational modeling, Object detection, Detection and localization in 2D and 3D, Datasets and evaluation BibRef

Wang, K.[Keyang], Zhang, L.[Lei],
Reconcile Prediction Consistency for Balanced Object Detection,
ICCV21(3611-3620)
IEEE DOI 2203
Location awareness, Training, Shape, Detectors, Object detection, Benchmark testing, Detection and localization in 2D and 3D, Recognition and classification BibRef

Zhao, X.Y.[Xiang-Yun], Zou, X.[Xu], Wu, Y.[Ying],
Morphable Detector for Object Detection on Demand,
ICCV21(4751-4760)
IEEE DOI 2203
Training, Visualization, Embedded systems, Semantics, Prototypes, Object detection, Vision applications and systems, Detection and localization in 2D and 3D BibRef

Meng, M.[Meng], Zhang, T.Z.[Tian-Zhu], Tian, Q.[Qi], Zhang, Y.D.[Yong-Dong], Wu, F.[Feng],
Foreground Activation Maps for Weakly Supervised Object Localization,
ICCV21(3365-3375)
IEEE DOI 2203
Location awareness, Scalability, Computational modeling, Benchmark testing, Task analysis, Standards, Recognition and classification BibRef

Qiu, H.Q.[He-Qian], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Cui, J.H.[Jian-Hua], Song, Z.C.[Zi-Chen], Wang, L.X.[Lan-Xiao], Zhang, M.J.[Min-Jian],
CrossDet: Crossline Representation for Object Detection,
ICCV21(3175-3184)
IEEE DOI 2203
Training, Location awareness, Codes, Object detection, Interference, Detectors, Detection and localization in 2D and 3D, Scene analysis and understanding BibRef

Gao, W.[Wei], Wan, F.[Fang], Pan, X.J.[Xing-Jia], Peng, Z.L.[Zhi-Liang], Tian, Q.[Qi], Han, Z.J.[Zhen-Jun], Zhou, B.[Bolei], Ye, Q.X.[Qi-Xiang],
TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization,
ICCV21(2866-2875)
IEEE DOI 2203
Location awareness, Couplings, Visualization, Fuses, Convolution, Semantics, Transformers, Detection and localization in 2D and 3D, Recognition and classification BibRef

Ki, M.S.[Min-Song], Uh, Y.J.[Young-Jung], Choe, J.[Junsuk], Byun, H.R.[Hye-Ran],
Contrastive Attention Maps for Self-supervised Co-localization,
ICCV21(2783-2792)
IEEE DOI 2203
Training, Representation learning, Codes, Computational modeling, Aggregates, Dogs, Detection and localization in 2D and 3D, BibRef

Xie, J.H.[Jin-Heng], Luo, C.[Cheng], Zhu, X.P.[Xiang-Ping], Jin, Z.Q.[Zi-Qi], Lu, W.Z.[Wei-Zeng], Shen, L.L.[Lin-Lin],
Online Refinement of Low-level Feature Based Activation Map for Weakly Supervised Object Localization,
ICCV21(132-141)
IEEE DOI 2203
Location awareness, Uncertainty, Codes, Drives, Generators, Entropy, Recognition and classification, Detection and localization in 2D and 3D BibRef

Park, S.[Sanghun], Kim, K.[Kunhee], Lee, E.[Eunseop], Kim, D.J.[Dai-Jin],
Localization Uncertainty-Based Attention for Object Detection,
ICIP21(2224-2228)
IEEE DOI 2201
Location awareness, Uncertainty, Detectors, Object detection, Predictive models, Benchmark testing, Object detection, Uncertainty attention module BibRef

Roh, B.[Byungseok], Shin, W.[Wuhyun], Kim, I.[Ildoo], Kim, S.[Sungwoong],
Spatially Consistent Representation Learning,
CVPR21(1144-1153)
IEEE DOI 2111

WWW Link. Code, Classification. Location awareness, Learning systems, Image segmentation, Codes, Object detection, Benchmark testing BibRef

Pan, X.J.[Xing-Jia], Gao, Y.G.[Ying-Guo], Lin, Z.W.[Zhi-Wen], Tang, F.[Fan], Dong, W.M.[Wei-Ming], Yuan, H.[Haolei], Huang, F.Y.[Fei-Yue], Xu, C.S.[Chang-Sheng],
Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization,
CVPR21(11637-11646)
IEEE DOI 2111
Location awareness, Convolutional codes, Correlation, Aggregates, Random access memory, Benchmark testing BibRef

Wei, J.[Jun], Wang, Q.[Qin], Li, Z.[Zhen], Wang, S.[Sheng], Zhou, S.K.[S. Kevin], Cui, S.G.[Shu-Guang],
Shallow Feature Matters for Weakly Supervised Object Localization,
CVPR21(5989-5997)
IEEE DOI 2111
Location awareness, Image segmentation, Image color analysis, Object detection, Interference, Predictive models, Feature extraction BibRef

Huang, Z.Y.[Zhao-Yang], Zhou, H.[Han], Li, Y.J.[Yi-Jin], Yang, B.B.[Bang-Bang], Xu, Y.[Yan], Zhou, X.W.[Xiao-Wei], Bao, H.J.[Hu-Jun], Zhang, G.F.[Guo-Feng], Li, H.S.[Hong-Sheng],
VS-Net: Voting with Segmentation for Visual Localization,
CVPR21(6097-6107)
IEEE DOI 2111
Location awareness, Training, Visualization, Image segmentation, Robot kinematics BibRef

Guo, G.Y.[Guang-Yu], Han, J.W.[Jun-Wei], Wan, F.[Fang], Zhang, D.W.[Ding-Wen],
Strengthen Learning Tolerance for Weakly Supervised Object Localization,
CVPR21(7399-7408)
IEEE DOI 2111
Location awareness, Visualization, Computational modeling, Semantics, Robustness, Pattern recognition BibRef

Keser, M.[Mert], Schwalbe, G.[Gesina], Nowzad, A.[Azarm], Knoll, A.[Alois],
Interpretable Model-Agnostic Plausibility Verification for 2D Object Detectors Using Domain-Invariant Concept Bottleneck Models,
SAIAD23(3891-3900)
IEEE DOI 2309
BibRef

Banik, S.[Soubarna], Lauri, M.[Mikko], Knoll, A.[Alois], Frintrop, S.[Simone],
Object Localization with Attribute Preference Based on Top-Down Attention,
CVS21(28-40).
Springer DOI 2109
BibRef

Kou, Z.Y.[Zi-Yi], Cui, G.F.[Guo-Feng], Wang, S.J.[Shao-Jie], Zhao, W.T.[Wen-Tian], Xu, C.L.[Chen-Liang],
Improve CAM with Auto-Adapted Segmentation and Co-Supervised Augmentation,
WACV21(3597-3605)
IEEE DOI 2106
CAM: Class Activation Map. Location awareness, Measurement, Image segmentation, Computational modeling, Benchmark testing BibRef

Zheng, Z.H.[Zhao-Heng], Sadhu, A.[Arka], Nevatia, R.[Ram],
Improving Object Detection and Attribute Recognition By Feature Entanglement Reduction,
ICIP21(2214-2218)
IEEE DOI 2201
Visualization, Head, Image color analysis, Computational modeling, Pipelines, Genomics, Object detection, Object Detection, Attribute Recognition BibRef

Babar, S.[Sadbhavana], Das, S.[Sukhendu],
Where to Look?: Mining Complementary Image Regions for Weakly Supervised Object Localization,
WACV21(1009-1018)
IEEE DOI 2106
Location awareness, Training, Visualization, Adaptation models, Fuses, Conferences BibRef

Zhang, Z.F.[Zhen-Fei], Bui, T.D.[Tien D.],
Attention-based Selection Strategy for Weakly Supervised Object Localization,
ICPR21(10305-10311)
IEEE DOI 2105
Location awareness, Training, Image recognition, Design methodology, Pattern recognition, Task analysis, attention-based selection strategy BibRef

Meethal, A.[Akhil], Pedersoli, M.[Marco], Belharbi, S.[Soufiane], Granger, E.[Eric],
Convolutional STN for Weakly Supervised Object Localization,
ICPR21(10157-10164)
IEEE DOI 2105
Location awareness, Training, Object detection, Benchmark testing, Recycling, Pattern recognition, Task analysis BibRef

Bojko, A.[Adrian], Dupont, R.[Romain], Tamaazousti, M.[Mohamed], Le Borgne, H.[Hervé],
Learning to Segment Dynamic Objects using SLAM Outliers,
ICPR21(9780-9787)
IEEE DOI 2105
Measurement, Training, Simultaneous localization and mapping, Runtime, Motion estimation, Dynamics, Semantics BibRef

Vanderschueren, A.[Antoine], Joos, V.[Victor], de Vleeschouwer, C.[Christophe],
Mutual Use of Semantics and Geometry for CNN-based Object Localization in Tof Images,
CARE20(202-217).
Springer DOI 2103
BibRef

Ki, M.S.[Min-Song], Uh, Y.J.[Young-Jung], Lee, W.[Wonyoung], Byun, H.R.[Hye-Ran],
In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization,
ACCV20(IV:3-18).
Springer DOI 2103
BibRef

Zhang, H.[Heng], Fromont, E.[Elisa], Lefevre, S.[Sébastien], Avignon, B.[Bruno],
Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection,
ACCV20(IV:104-118).
Springer DOI 2103
BibRef

Bae, W.[Wonho], Noh, J.[Junhyug], Kim, G.[Gunhee],
Rethinking Class Activation Mapping for Weakly Supervised Object Localization,
ECCV20(XV:618-634).
Springer DOI 2011
BibRef

Lu, W.Z.[Wei-Zeng], Jia, X.[Xi], Xie, W.C.[Wei-Cheng], Shen, L.L.[Lin-Lin], Zhou, Y.C.[Yi-Cong], Duan, J.M.[Jin-Ming],
Geometry Constrained Weakly Supervised Object Localization,
ECCV20(XXVI:481-496).
Springer DOI 2011
BibRef

Wu, Y., Chen, Y., Yuan, L., Liu, Z., Wang, L., Li, H., Fu, Y.,
Rethinking Classification and Localization for Object Detection,
CVPR20(10183-10192)
IEEE DOI 2008
Proposals, Correlation, Task analysis, Convolution, Feature extraction, Detectors, Robustness BibRef

Spencer, J., Bowden, R., Hadfield, S.,
Same Features, Different Day: Weakly Supervised Feature Learning for Seasonal Invariance,
CVPR20(6458-6467)
IEEE DOI 2008
Training, Measurement, Machine learning, Feature extraction, Simultaneous localization and mapping, Task analysis BibRef

Mai, J., Yang, M., Luo, W.,
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization,
CVPR20(8763-8772)
IEEE DOI 2008
Training, Visualization, Classification algorithms, Supervised learning, Task analysis, Semantics BibRef

Strecke, M., Stückler, J.,
Where Does It End?: Reasoning About Hidden Surfaces by Object Intersection Constraints,
CVPR20(9589-9597)
IEEE DOI 2008
Surface reconstruction, Shape, Image reconstruction, Simultaneous localization and mapping, Minimization BibRef

Cai, M., Reid, I.D.,
Reconstruct Locally, Localize Globally: A Model Free Method for Object Pose Estimation,
CVPR20(3150-3160)
IEEE DOI 2008
Solid modeling, Head, Pose estimation, Image reconstruction, Cameras BibRef

Choe, J.[Junsuk], Oh, S.J.[Seong Joon], Lee, S.[Seungho], Chun, S.[Sanghyuk], Akata, Z.[Zeynep], Shim, H.J.[Hyun-Jung],
Evaluating Weakly Supervised Object Localization Methods Right,
CVPR20(3130-3139)
IEEE DOI 2008
Task analysis, Protocols, Measurement, Training, Benchmark testing, Predictive models BibRef

Zhang, C., Cao, Y., Wu, J.,
Rethinking the Route Towards Weakly Supervised Object Localization,
CVPR20(13457-13466)
IEEE DOI 2008
Task analysis, Computational modeling, Pipelines, Detectors, Training, Noise measurement BibRef

Zhao, Y., Li, J., Zhang, Y., Tian, Y.,
Multi-Class Part Parsing With Joint Boundary-Semantic Awareness,
ICCV19(9176-9185)
IEEE DOI 2004
feature selection, image segmentation, object detection, accurate part localization, high-level feature fusion, Decoding BibRef

Visser, J., Corbetta, A., Menkovski, V., Toschi, F.,
Stampnet: Unsupervised Multi-Class Object Discovery,
ICIP19(2951-2955)
IEEE DOI 1910
object discovery, unsupervised learning, image localization, image clustering BibRef

Kim, J.U., Park, S., Ro, Y.M.,
Towards Human-Like Interpretable Object Detection Via Spatial Relation Encoding,
ICIP20(3284-3288)
IEEE DOI 2011
Visualization, Feature extraction, Detectors, Cognition, Object detection, Birds, Visual interpretation, human-like BibRef

Kim, J.U., Ro, Y.M.[Y. Man],
Attentive Layer Separation for Object Classification and Object Localization in Object Detection,
ICIP19(3995-3999)
IEEE DOI 1910
Object detection, Attention network, Object classification, Object localization, Layer separation BibRef

Kao, C.C.[Chieh-Chi], Lee, T.Y.[Teng-Yok], Sen, P.[Pradeep], Liu, M.Y.[Ming-Yu],
Localization-Aware Active Learning for Object Detection,
ACCV18(VI:506-522).
Springer DOI 1906
BibRef

Jiang, B.R.[Bo-Rui], Luo, R.X.[Rui-Xuan], Mao, J.Y.[Jia-Yuan], Xiao, T.[Tete], Jiang, Y.N.[Yu-Ning],
Acquisition of Localization Confidence for Accurate Object Detection,
ECCV18(XIV: 816-832).
Springer DOI 1810
BibRef

Li, H., Liu, Y., Zhang, X., An, Z., Wang, J., Chen, Y., Tong, J.,
Do we really need more training data for object localization,
ICIP17(775-779)
IEEE DOI 1803
Feature extraction, Image resolution, Machine learning, Proposals, Semantics, Training, Training data, Deep learning, object localization BibRef

Lu, Y.[Ya], Zhao, J.[Ji], Ma, J.Y.[Jia-Yi],
Object localization by density-based spatial clustering,
VCIP16(1-4)
IEEE DOI 1701
Clustering algorithms BibRef

Lu, C.[Cewu], Lu, Y.Y.[Yong-Yi], Chen, H.[Hao], Tang, C.K.[Chi-Keung],
Square Localization for Efficient and Accurate Object Detection,
ICCV15(2560-2568)
IEEE DOI 1602
Find square objects. BibRef

Long, C.J.[Cheng-Jiang], Wang, X.Y.[Xiao-Yu], Hua, G.[Gang], Yang, M.[Ming], Lin, Y.Q.[Yuan-Qing],
Accurate Object Detection with Location Relaxation and Regionlets Re-localization,
ACCV14(I: 260-275).
Springer DOI 1504
BibRef

Bilen, H.[Hakan], Pedersoli, M.[Marco], Tuytelaars, T.[Tinne],
Weakly supervised object detection with convex clustering,
CVPR15(1081-1089)
IEEE DOI 1510
BibRef
Earlier:
Weakly Supervised Detection with Posterior Regularization,
BMVC14(xx-yy).
HTML Version. 1410
object localization BibRef

Shi, M.J.[Miao-Jing], Caesar, H., Ferrari, V.[Vittorio],
Weakly Supervised Object Localization Using Things and Stuff Transfer,
ICCV17(3401-3410)
IEEE DOI 1802
image classification, image representation, image segmentation, learning (artificial intelligence), object detection, Training BibRef

Shi, M.J.[Miao-Jing], Ferrari, V.[Vittorio],
Weakly Supervised Object Localization Using Size Estimates,
ECCV16(V: 105-121).
Springer DOI 1611
BibRef

Zhang, Z.Q.[Zhi-Qi], Cao, Y.[Yu], Salvi, D.[Dhaval], Oliver, K.[Kenton], Waggoner, J.W.[Jarrell W.], Wang, S.[Song],
Free-shape subwindow search for object localization,
CVPR10(1086-1093).
IEEE DOI 1006
BibRef

Yang, Y.C.[Yan-Chao], Lai, B.[Brian], Soatto, S.[Stefano],
DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping*,
CVPR21(2825-2835)
IEEE DOI 2111
Training, Image segmentation, Motion segmentation, Computational modeling, Object segmentation, Object detection, Turning BibRef

Fulkerson, B.[Brian], Vedaldi, A.[Andrea], Soatto, S.[Stefano],
Class Segmentation and Object Localization with Superpixel Neighborhoods,
ICCV09(670-677).
IEEE DOI 0909
BibRef
Earlier:
Localizing Objects with Smart Dictionaries,
ECCV08(I: 179-192).
Springer DOI 0810
Category and location of objects. First pixel classification with reduced dictionary. Combined results. BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
One-Shot Object Detection, Single Shot Detector, and Segmentation .


Last update:Jan 30, 2024 at 20:33:16