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Saliency
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1707
Patch, feature, learning
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Cholakkal, H.[Hisham],
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1810
convolution, feature extraction, feedforward neural nets,
image classification, object detection, probability,
CNN image classifier
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Visual attribute
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2103
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IEEE DOI
1805
Analytical models, Computational complexity,
Computational modeling, Fuses, Labeling, Object detection,
weak prediction
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IEEE DOI
1909
Saliency detection, Generators, Training data, Training,
Feature extraction, Proposals, Task analysis,
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Elsevier DOI
2005
Salient object detection, Webly-supervised learning, Deep learning
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A progressive learning framework based on single-instance annotation
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Elsevier DOI
2003
Single-instance annotation, Progressive learning framework,
Weakly supervised object detection, Instance mining
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Liu, Y.X.[Yu-Xuan],
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Weakly-Supervised Salient Object Detection With Saliency Bounding
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IP(30), 2021, pp. 4423-4435.
IEEE DOI
2104
Object detection, Annotations, Detectors, Training, Proposals,
Computer science, Task analysis, Saliency bounding boxes,
weak supervision
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Zheng, X.Y.[Xiao-Yang],
Tan, X.[Xin],
Zhou, J.[Jie],
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CirSysVideo(31), No. 11, November 2021, pp. 4370-4380.
IEEE DOI
2112
Saliency detection, Task analysis, Object detection,
Feature extraction, Training, Image segmentation, Annotations,
object subitizing
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Liang, Z.J.[Zi-Jian],
Wang, P.J.[Peng-Jie],
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Weakly-Supervised Salient Object Detection on Light Fields,
IP(31), 2022, pp. 6295-6305.
IEEE DOI
2210
Light fields, Saliency detection, Object detection, Annotations,
Visualization, Image color analysis, Feature extraction, weak supervision
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He, S.F.[Sheng-Feng],
Lau, R.W.H.[Rynson W. H.],
Exemplar-Driven Top-Down Saliency Detection via Deep Association,
CVPR16(5723-5732)
IEEE DOI
1612
BibRef
Earlier:
Saliency Detection with Flash and No-flash Image Pairs,
ECCV14(III: 110-124).
Springer DOI
1408
Only closer (foreground or salient) objects are well lit by the flash.
BibRef
Zhou, Z.H.[Zhi-Heng],
Guo, Y.F.[Yong-Fan],
Dai, M.[Ming],
Huang, J.C.[Jun-Chu],
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IET-IPR(15), No. 9, 2021, pp. 1957-1970.
DOI Link
2106
BibRef
Dong, B.[Bowen],
Huang, Z.T.[Zi-Tong],
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Boosting Weakly Supervised Object Detection via Learning Bounding Box
Adjusters,
ICCV21(2856-2865)
IEEE DOI
2203
Training, Location awareness, Codes, Computational modeling,
Object detection, Classification algorithms,
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Zhang, L.[Libao],
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Salient Object Detection Based on Progressively Supervised Learning
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GeoRS(59), No. 11, November 2021, pp. 9682-9696.
IEEE DOI
2111
Annotations, Training, Supervised learning, Remote sensing,
Object detection, Image segmentation, Feature extraction,
weakly supervised learning (WSL)
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Zhang, Y.Z.[Yun-Zhou],
Wang, Z.Y.[Zhen-Yu],
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Kerr, D.[Dermot],
Complementary Characteristics Fusion Network for Weakly Supervised
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IVC(126), 2022, pp. 104536.
Elsevier DOI
2209
Salient object detection, Weakly supervised learning,
Edge fusion module, Feature correlation module,
Self-supervised salient detection loss
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Yang, J.[Jie],
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Qi, Z.Q.[Zhi-Quan],
Learning deep feature correspondence for unsupervised anomaly
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PR(132), 2022, pp. 108874.
Elsevier DOI
2209
Anomaly detection, Anomaly segmentation,
Feature correspondence, Dual network
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Multiple instance learning on deep features for weakly supervised
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CVIU(214), 2022, pp. 103299.
Elsevier DOI
2112
Deep learning, Convolutional neural networks,
Weakly supervised object detection, Non-photographic images,
Multiple instance learning
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Wen, J.[Jie],
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Yang, J.[Jian],
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Selecting High-Quality Proposals for Weakly Supervised Object
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IP(32), 2023, pp. 682-693.
IEEE DOI
2301
Proposals, Training, Object detection, Loss measurement, Detectors,
Feature extraction, Phase measurement,
high-quality supervision
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Zhou, H.J.[Hua-Jun],
Chen, P.J.[Pei-Jia],
Yang, L.X.[Ling-Xiao],
Xie, X.H.[Xiao-Hua],
Lai, J.H.[Jian-Huang],
Activation to Saliency: Forming High-Quality Labels for Unsupervised
Salient Object Detection,
CirSysVideo(33), No. 2, February 2023, pp. 743-755.
IEEE DOI
2302
Detectors, Feature extraction, Semantics, Training, Object detection,
Task analysis, Random access memory,
adaptive decision boundary
BibRef
Zhou, H.J.[Hua-Jun],
Qiao, B.[Bo],
Yang, L.X.[Ling-Xiao],
Lai, J.H.[Jian-Huang],
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Texture-Guided Saliency Distilling for Unsupervised Salient Object
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CVPR23(7257-7267)
IEEE DOI
2309
BibRef
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Qin, Q.[Qi],
Zhang, C.[Chen],
Jiang, Q.P.[Qiu-Ping],
Wang, S.Q.[Shi-Qi],
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Kwong, S.[Sam],
A Weakly Supervised Learning Framework for Salient Object Detection
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CirSysVideo(33), No. 2, February 2023, pp. 534-548.
IEEE DOI
2302
Training, Task analysis, Object detection, Decoding, Annotations,
Urban areas, Information science, Salient object detection,
group-wise incremental mechanism
BibRef
Pang, Y.[Yu],
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Wu, H.[Hao],
Yu, X.[Xiaosheng],
Unsupervised Multi-Subclass Saliency Classification for Salient
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MultMed(25), 2023, pp. 2189-2202.
IEEE DOI
2306
Training, Object detection, Task analysis, Predictive models, Automobiles,
Saliency detection, Manuals, spatial smoothness
BibRef
Liu, Z.F.[Zhou-Feng],
Wang, K.H.[Kai-Hua],
Li, C.L.[Chun-Lei],
Ding, S.M.[Shun-Min],
Xi, J.T.[Jiang-Tao],
Triple critical feature capture network: A triple critical feature
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IET-CV(17), No. 8, 2023, pp. 895-912.
DOI Link
2312
image processing, object detection
BibRef
Xu, B.W.[Bin-Wei],
Liang, H.R.[Hao-Ran],
Gong, W.H.[Wei-Hua],
Liang, R.H.[Rong-Hua],
Chen, P.[Peng],
A Visual Representation-Guided Framework With Global Affinity for
Weakly Supervised Salient Object Detection,
CirSysVideo(34), No. 1, January 2024, pp. 248-259.
IEEE DOI
2401
BibRef
Wu, Z.H.[Zhi-Hao],
Wen, J.[Jie],
Xu, Y.[Yong],
Yang, J.[Jian],
Zhang, D.[David],
Multiple Instance Detection Networks With Adaptive Instance
Refinement,
MultMed(25), 2023, pp. 267-279.
IEEE DOI
2301
Proposals, Training, Annotations, Object detection, Adaptive systems,
Benchmark testing, Detectors, Weakly supervised object detection,
proposal score
BibRef
Liang, S.[Shuang],
Yan, Z.Q.[Zhi-Qi],
Xie, C.[Chi],
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Wang, J.W.[Jie-Wen],
Scribble-based complementary graph reasoning network for weakly
supervised salient object detection,
CVIU(243), 2024, pp. 103977.
Elsevier DOI
2405
Salient object detection, Weakly supervision, Graph learning, Cross fusion
BibRef
Wu, Z.H.[Zhi-Hao],
Xu, Y.[Yong],
Yang, J.[Jian],
Li, X.L.[Xue-Long],
Misclassification in Weakly Supervised Object Detection,
IP(33), 2024, pp. 3413-3427.
IEEE DOI
2406
Proposals, Training, Automobiles, Semantics, Object detection,
Detectors, Cows, Weakly supervised object detection, semantics
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Liu, Y.[Yi],
Zhou, L.[Ling],
Wu, G.S.[Geng-Shen],
Xu, S.K.[Shou-Kun],
Han, J.G.[Jun-Gong],
TCGNet: Type-Correlation Guidance for Salient Object Detection,
ITS(25), No. 7, July 2024, pp. 6633-6644.
IEEE DOI Code:
WWW Link.
2407
Object detection, Semantics, Correlation, Feature extraction,
Task analysis, Decoding, Routing, Salient object detection, capsule network
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Asheghi, B.[Bahareh],
Salehpour, P.[Pedram],
Khiavi, A.M.[Abdolhamid Moallemi],
Hashemzadeh, M.[Mahdi],
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DASOD: Detail-aware salient object detection,
IVC(148), 2024, pp. 105154.
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WWW Link.
2407
Conditional variational auto-encoder,
Uncertainty quantification, Refinement network, SOD
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Veksler, O.[Olga],
Test Time Adaptation with Regularized Loss for Weakly Supervised
Salient Object Detection,
CVPR23(7360-7369)
IEEE DOI
2309
BibRef
Lin, Z.W.[Zhi-Wei],
Yang, Z.Y.[Zeng-Yu],
Wang, Y.T.[Yong-Tao],
Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised
Object Discovery with Transformers,
WACV23(4032-4042)
IEEE DOI
2302
WWW Link. Location awareness, Visualization, Aggregates, Detectors,
Object detection, Transformers
BibRef
Wang, Y.F.[Yi-Fan],
Zhang, W.B.[Wen-Bo],
Wang, L.J.[Li-Jun],
Liu, T.[Ting],
Lu, H.C.[Hu-Chuan],
Multi-Source Uncertainty Mining for Deep Unsupervised Saliency
Detection,
CVPR22(11717-11726)
IEEE DOI
2210
Adaptation models, Uncertainty, Computer network reliability,
Training data, Object detection, Reliability engineering,
Self- semi- meta- unsupervised learning
BibRef
Wang, Z.D.[Zhen-Dong],
Chen, Z.[Zhenyuan],
Gong, C.[Chen],
Class Activation Map Refinement via Semantic Affinity Exploration for
Weakly Supervised Object Detection,
ICIP22(4168-4172)
IEEE DOI
2211
Location awareness, Semantics, Collaboration, Object detection,
Detectors, Benchmark testing, class activation map
BibRef
Hou, L.[Luwei],
Zhang, Y.[Yu],
Fu, K.[Kui],
Li, J.[Jia],
Informative and Consistent Correspondence Mining for Cross-Domain
Weakly Supervised Object Detection,
CVPR21(9924-9933)
IEEE DOI
2111
Annotations, Collaboration, Object detection,
Detectors, Generators
BibRef
Li, L.T.B.[Lv Tang Bo],
Zhong, Y.J.[Yi-Jie],
Ding, S.H.[Shou-Hong],
Song, M.[Mofei],
Disentangled High Quality Salient Object Detection,
ICCV21(3560-3570)
IEEE DOI
2203
Training, Deep learning, Uncertainty, Semantics, Refining,
Graphics processing units,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Ouyang, S.X.[Sheng-Xiong],
Wang, X.L.[Xing-Lu],
Lyu, K.[Kejie],
Li, Y.M.[Ying-Ming],
Pseudo-Label Generation-Evaluation Framework for Cross Domain Weakly
Supervised Object Detection,
ICIP21(724-728)
IEEE DOI
2201
Annotations, Image processing, Detectors, Object detection,
Task analysis, Cross domain, Weakly supervised, Object detection, Evaluator
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Shen, Y.H.[Yun-Hang],
Ji, R.R.[Rong-Rong],
Wang, Y.[Yan],
Chen, Z.W.[Zhi-Wei],
Zheng, F.[Feng],
Huang, F.Y.[Fei-Yue],
Wu, Y.S.[Yun-Sheng],
Enabling Deep Residual Networks for Weakly Supervised Object Detection,
ECCV20(VIII:118-136).
Springer DOI
2011
BibRef
Kosugi, S.,
Yamasaki, T.,
Aizawa, K.,
Object-Aware Instance Labeling for Weakly Supervised Object Detection,
ICCV19(6063-6071)
IEEE DOI
2004
image annotation, image classification, iterative methods,
learning (artificial intelligence), object detection, Focusing
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Inoue, N.,
Furuta, R.,
Yamasaki, T.,
Aizawa, K.,
Cross-Domain Weakly-Supervised Object Detection Through Progressive
Domain Adaptation,
CVPR18(5001-5009)
IEEE DOI
1812
Object detection, Task analysis, Detectors, Dogs, Search engines,
Feature extraction, Noise measurement
BibRef
Zhang, D.,
Han, J.,
Zhang, Y.,
Supervision by Fusion: Towards Unsupervised Learning of Deep Salient
Object Detector,
ICCV17(4068-4076)
IEEE DOI
1802
convolution, image fusion, neural nets, object detection,
unsupervised learning, DNNs, deep convolutional models,
Unsupervised learning
BibRef
López-Sastre, R.J.[Roberto J.],
Unsupervised Robust Feature-Based Partition Ensembling to Discover
Categories,
Robust16(1187-1195)
IEEE DOI
1612
Different features to aggregate different partitions to get objects.
BibRef
Cholakkal, H.[Hisham],
Johnson, J.[Jubin],
Rajan, D.[Deepu],
Backtracking ScSPM Image Classifier for Weakly Supervised Top-Down
Saliency,
CVPR16(5278-5287)
IEEE DOI
1612
BibRef
Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Color, Multispectral, RGB, for Salient Regions .