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Segment anything model (SAM) has achieved great success in the field of natural image segmentation.
J. Stander, R. Mech, and J. Ostermann, “Detection of moving cast shadows for object segmentation,”
1999
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S.-Y. Chien, S.-Y. Ma, and L.-G. Chen, “Efficient moving object segmentation algorithm using background registration technique,”
2002
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A. Elgammal, R. Duraiswami, D. Harwood, and L. Davis, “Background and foreground modeling using nonparametric kernel density estimation for visual surveillance,”
2002
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P. Kumar, K. Sengupta, and A. Lee, “A comparative study of different color spaces for foreground and shadow detection for traffic monitoring system,” in
2002
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C.-C. Thien and J.-C. Lin, “An image-sharing method with user-friendly shadow images,”
2003
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R. Cucchiara, C. Grana, M. Piccardi, and A. Prati, “Detecting moving objects, ghosts, and shadows in video streams,”
2003
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S. Nadimi and B. Bhanu, “Physical models for moving shadow and object detection in video,”
2004
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E. Salvador, A. Cavallaro, and T. Ebrahimi, “Cast shadow segmentation using invariant color features,”
2004
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J. C. S. Jacques, C. R. Jung, and S. R. Musse, “Background subtraction and shadow detection in grayscale video sequences,” in
2005
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D. Xu, J. Liu, X. Li, Z. Liu, and X. Tang, “Insignificant shadow detection for video segmentation,”
2005
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I. N. Junejo and H. Foroosh, “Estimating geo-temporal location of stationary cameras using shadow trajectories,” in
2008
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J.-F. Lalonde, A. A. Efros, and S. G. Narasimhan, “Estimating natural illumination from a single outdoor image,” in
2009
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A. Panagopoulos, D. Samaras, and N. Paragios, “Robust shadow and illumination estimation using a mixture model,” in
2009
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T. Okabe, I. Sato, and Y. Sato, “Attached shadow coding: Estimating surface normals from shadows under unknown reflectance and lighting conditions,” in
2009
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T. Okabe, I. Sato, and Y. Sato, “Attached shadow coding: Estimating surface normals from shadows under unknown reflectance and lighting conditions,” in
2009
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Y. Wang, “Real-time moving vehicle detection with cast shadow removal in video based on conditional random field,”
2009
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J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in
2009
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L. Wu, X. Cao, and H. Foroosh, “Camera calibration and geo-location estimation from two shadow trajectories,”
2010
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X. Huang, G. Hua, J. Tumblin, and L. Williams, “What characterizes a shadow boundary under the sun and sky?” in
2011
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Z. Liu, K. Huang, and T. Tan, “Cast shadow removal in a hierarchical manner using mrf,”
2011
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Lalonde, Jean-François and Efros, Alexei A and Narasimhan, Srinivasa G, “Estimating the natural illumination conditions from a single outdoor image,”
2012
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A. Ecins, C. Fermüller, and Y. Aloimonos, “Shadow free segmentation in still images using local density measure,” in
2014
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S. Nowozin, “Optimal decisions from probabilistic models: the intersection-over-union case,” in
2014
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D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,”
2014
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T. F. Y. Vicente, L. Hou, C.-P. Yu, M. Hoai, and D. Samaras, “Large-scale training of shadow detectors with noisily-annotated shadow examples,” in
2016
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D. Hendrycks and K. Gimpel, “Gaussian error linear units (GELUs),”
2016
Cited alongside, same era.
J. L. Ba, J. R. Kiros, and G. E. Hinton, “Layer normalization,”
2016
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M. A. Rahman and Y. Wang, “Optimizing intersection-over-union in deep neural networks for image segmentation,” in
2016
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2017
Cited alongside, same era.
M. Russell, J. J. Zou, G. Fang, and W. Cai, “Feature-based image patch classification for moving shadow detection,”
2017
Cited alongside, same era.
N. Carion, F. Massa, G. Synnaeve, N. Usunier, A. Kirillov, and S. Zagoruyko, “End-to-end object detection with transformers,” in
2020
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C. Raffel, N. Shazeer, A. Roberts, K. Lee, S. Narang, M. Matena, Y. Zhou, W. Li, and P. J. Liu, “Exploring the limits of transfer learning with a unified text-to-text transformer,”
2020
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L. Zhu, K. Xu, Z. Ke, and R. W. Lau, “Mitigating intensity bias in shadow detection via feature decomposition and reweighting,” in
2021
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Z. Chen, L. Wan, L. Zhu, J. Shen, H. Fu, W. Liu, and J. Qin, “Triple-cooperative video shadow detection,” in
2021
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Z. Yang, Y. Wei, and Y. Yang, “Associating objects with transformers for video object segmentation,”
2021
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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,”
2017
Cited alongside, same era.
T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie, “Feature pyramid networks for object detection,” in
2017
Cited alongside, same era.
H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia, “Pyramid scene parsing network,” in
2017
Cited alongside, same era.
Q. Hou, M.-M. Cheng, X. Hu, A. Borji, Z. Tu, and P. H. Torr, “Deeply supervised salient object detection with short connections,” in
2017
Cited alongside, same era.
X. Hu, L. Zhu, C.-W. Fu, J. Qin, and P.-A. Heng, “Direction-aware spatial context features for shadow detection,” in
2018
Cited alongside, same era.
L. Zhu, Z. Deng, X. Hu, C.-W. Fu, X. Xu, J. Qin, and P.-A. Heng, “Bidirectional feature pyramid network with recurrent attention residual modules for shadow detection,” in
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Y. Mao, N. Wang, W. Zhou, and H. Li, “Joint inductive and transductive learning for video object segmentation,” in
2021
Later among the works it cites.
X. Hu, T. Wang, C.-W. Fu, Y. Jiang, Q. Wang, and P.-A. Heng, “Revisiting shadow detection: A new benchmark dataset for complex world,”
2021
Later among the works it cites.
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly
2021
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Y. Wang, Z. Xu, X. Wang, C. Shen, B. Cheng, H. Shen, and H. Xia, “End-to-end video instance segmentation with transformers,” in
2021
Later among the works it cites.
X. Zhu, W. Su, L. Lu, B. Li, X. Wang, and J. Dai, “Deformable DETR: Deformable transformers for end-to-end object detection,” in
2021
Later among the works it cites.
Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, and B. Guo, “Swin transformer: Hierarchical vision transformer using shifted windows,” in
2021
Later among the works it cites.
2021
Later among the works it cites.
A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark
2021
Later among the works it cites.
M. Patrick, D. Campbell, Y. Asano, I. Misra, F. Metze, C. Feichtenhofer, A. Vedaldi, and J. F. Henriques, “Keeping your eye on the ball: Trajectory attention in video transformers,”
2021
Later among the works it cites.
X. Ding, J. Yang, X. Hu, and X. Li, “Learning shadow correspondence for video shadow detection,” in
2022
Later among the works it cites.
H. K. Cheng and A. G. Schwing, “XMem: Long-term video object segmentation with an atkinson-shiffrin memory model,” in
2022
Later among the works it cites.
X. Xu, J. Wang, X. Li, and Y. Lu, “Reliable propagation-correction modulation for video object segmentation,” in
2022
Later among the works it cites.
S. Gao, C. Zhou, C. Ma, X. Wang, and J. Yuan, “AiATrack: Attention in attention for transformer visual tracking,” in
2022
Later among the works it cites.
X. Lu, Y. Cao, S. Liu, C. Long, Z. Chen, X. Zhou, Y. Yang, and C. Xiao, “Video shadow detection via spatio-temporal interpolation consistency training,” in
2022
Later among the works it cites.
2022
Later among the works it cites.
K. He, X. Chen, S. Xie, Y. Li, P. Dollár, and R. Girshick, “Masked autoencoders are scalable vision learners,” in
2022
Later among the works it cites.
2023
Closest in time.
L. Liu, J. Prost, L. Zhu, N. Papadakis, P. Liò, C.-B. Schönlieb, and A. I. Aviles-Rivero, “SCOTCH and SODA: A transformer video shadow detection framework,” in
2023
Closest in time.
L. Jie and H. Zhang, “RMLANet: Random multi-level attention network for shadow detection and removal,”
2023
Closest in time.