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While pre-trained large-scale vision models have shown significant promise for semantic correspondence, their features often struggle to grasp the geometry and orientation of instances.
Object recognition from local scale-invariant features
David G. Lowe · 1999
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Histograms of oriented gradients for human detection
Navneet Dalal and Bill Triggs · 2005
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The Caltech-UCSD birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Articulated human detection with flexible mixtures of parts
Yi Yang and Deva Ramanan · 2012
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Do convnets learn correspondence?
Jonathan L. Long, Ning Zhang, and Trevor Darrell · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Proposal flow
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Joint recovery of dense correspondence and cosegmentation in two images
Tatsunori Taniai, Sudipta N. Sinha, and Yoichi Sato · 2016
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Proposal flow: Semantic correspondences from object proposals
Bumsub Ham, Minsu Cho, Cordelia Schmid, and Jean Ponce · 2017
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End-to-end learning of geometry and context for deep stereo regression
Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta, Peter Henry, Ryan Kennedy, Abraham Bachrach, and Adam Bry · 2017
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Convolutional neural network architecture for geometric matching
Ignacio Rocco, Relja Arandjelović, and Josef Sivic · 2017
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Unsupervised learning of object frames by dense equivariant image labelling
James Thewlis, Hakan Bilen, and Andrea Vedaldi · 2017
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Object-aware dense semantic correspondence
Fan Yang, Xin Li, Hong Cheng, Jianping Li, and Leiting Chen · 2017
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Neural best-buddies: Sparse cross-domain correspondence
Kfir Aberman, Jing Liao, Mingyi Shi, Dani Lischinski, Baoquan Chen, and Daniel Cohen-Or · 2018
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Recurrent transformer networks for semantic correspondence
Seungryong Kim, Stephen Lin, Sang Ryul Jeon, Dongbo Min, and Kwanghoon Sohn · 2018
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End-to-end weakly-supervised semantic alignment
Ignacio Rocco, Relja Arandjelović, and Josef Sivic · 2018
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Attentive semantic alignment with offset-aware correlation kernels
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Scops: Self-supervised co-part segmentation
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Semantic attribute matching networks
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SFNet: Learning object-aware semantic correspondence
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Ilya Loshchilov and Frank Hutter · 2019
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Reference-based sketch image colorization using augmented-self reference and dense semantic correspondence
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Probabilistic warp consistency for weakly-supervised semantic correspondences
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Junsoo Lee, Eungyeup Kim, Yunsung Lee, Dongjun Kim, Jaehyuk Chang, and Jaegul Choo · 2020
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Semantic correspondence as an optimal transport problem
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Learning to compose hypercolumns for visual correspondence
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