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Recent progress in self-supervised representation learning has resulted in models that are capable of extracting image features that are not only effective at encoding image level, but also pixel-level, semantics.
Prism: A practical realtime imaging stereo matcher
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Multiple view geometry in computer vision
Richard Hartley and Andrew Zisserman · 2003
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Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
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Histograms of oriented gradients for human detection
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Accurate and efficient stereo processing by semi-global matching and mutual information
Heiko Hirschmuller · 2005
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Simultaneous object recognition and segmentation from single or multiple model views
Vittorio Ferrari, Tinne Tuytelaars, and Luc Van Gool · 2006
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Monoslam: Real-time single camera slam
Andrew J Davison, Ian D Reid, Nicholas D Molton, and Olivier Stasse · 2007
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Sift flow: Dense correspondence across different scenes
Ce Liu, Jenny Yuen, Antonio Torralba, Josef Sivic, and William T Freeman · 2008
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Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
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Large displacement optical flow from nearest neighbor fields
Zhuoyuan Chen, Hailin Jin, Zhe Lin, Scott Cohen, and Ying Wu · 2013
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Do convnets learn correspondence?
Jonathan L Long, Ning Zhang, and Trevor Darrell · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Unsupervised generation of a viewpoint annotated car dataset from videos
Nima Sedaghat and Thomas Brox · 2015
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Flowweb: Joint image set alignment by weaving consistent, pixel-wise correspondences
Tinghui Zhou, Yong Jae Lee, Stella X Yu, and Alyosha A Efros · 2015
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Universal correspondence network
Christopher B Choy, JunYoung Gwak, Silvio Savarese, and Manmohan Chandraker · 2016
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Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 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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Learning dense correspondence via 3d-guided cycle consistency
Tinghui Zhou, Philipp Krahenbuhl, Mathieu Aubry, Qixing Huang, and Alexei A Efros · 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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Scnet: Learning semantic correspondence
Kai Han, Rafael S Rezende, Bumsub Ham, Kwan-Yee K Wong, Minsu Cho, Cordelia Schmid, and Jean Ponce · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 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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Deep semantic feature matching
Nikolai Ufer and Bjorn Ommer · 2017
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Self-supervised 3d mesh reconstruction from single images
Tao Hu, Liwei Wang, Xiaogang Xu, Shu Liu, and Jiaya Jia · 2021
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Densepose 3d: Lifting canonical surface maps of articulated objects to the third dimension
Roman Shapovalov, David Novotny, Benjamin Graham, Patrick Labatut, and Andrea Vedaldi · 2021
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Multi-scale matching networks for semantic correspondence
Dongyang Zhao, Ziyang Song, Zhenghao Ji, Gangming Zhao, Weifeng Ge, and Yizhou Yu · 2021
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Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 2022
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Demystifying unsupervised semantic correspondence estimation
Mehmet Aygün and Oisin Mac Aodha · 2022
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Learning semantic correspondence with sparse annotations
Shuaiyi Huang, Luyu Yang, Bo He, Songyang Zhang, Xuming He, and Abhinav Shrivastava · 2022
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Learning to generate and reconstruct 3d meshes with only 2d supervision
Paul Henderson and Vittorio Ferrari · 2018
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Unsupervised learning of object landmarks through conditional image generation
Tomas Jakab, Ankush Gupta, Hakan Bilen, and Andrea Vedaldi · 2018
Cited alongside, same era.
Neighbourhood consensus networks
Ignacio Rocco, Mircea Cimpoi, Relja Arandjelović, Akihiko Torii, Tomas Pajdla, and Josef Sivic · 2018
Cited alongside, same era.
Discovery of latent 3d keypoints via end-to-end geometric reasoning
Supasorn Suwajanakorn, Noah Snavely, Jonathan J Tompson, and Mohammad Norouzi · 2018
Cited alongside, same era.
Canonical surface mapping via geometric cycle consistency
Nilesh Kulkarni, Abhinav Gupta, and Shubham Tulsiani · 2019
Cited alongside, same era.
Spair-71k: A large-scale benchmark for semantic correspondence
Juhong Min, Jongmin Lee, Jean Ponce, and Minsu Cho · 2019
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Share with thy neighbors: Single-view reconstruction by cross-instance consistency
Tom Monnier, Matthew Fisher, Alexei A Efros, and Mathieu Aubry · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Nerf-supervision: Learning dense object descriptors from neural radiance fields
Lin Yen-Chen, Pete Florence, Jonathan T Barron, Tsung-Yi Lin, Alberto Rodriguez, and Phillip Isola · 2022
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ibot: Image bert pre-training with online tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, and Tao Kong · 2022
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Asic: Aligning sparse in-the-wild image collections
Kamal Gupta, Varun Jampani, Carlos Esteves, Abhinav Shrivastava, Ameesh Makadia, Noah Snavely, and Abhishek Kar · 2023
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Unsupervised semantic correspondence using stable diffusion
Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, and Kwang Moo Yi · 2023
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Neural congealing: Aligning images to a joint semantic atlas
Dolev Ofri-Amar, Michal Geyer, Yoni Kasten, and Tali Dekel · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Learning universal semantic correspondences with no supervision and automatic data curation
Aleksandar Shtedritski, Andrea Vedaldi, and Christian Rupprecht · 2023
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Emergent correspondence from image diffusion
Luming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo, and Bharath Hariharan · 2023
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Teaching matters: Investigating the role of supervision in vision transformers
Matthew Walmer, Saksham Suri, Kamal Gupta, and Abhinav Shrivastava · 2023
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MagicPony: Learning articulated 3d animals in the wild
Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, and Andrea Vedaldi · 2023
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A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani, Deqing Sun, and Ming-Hsuan Yang · 2023
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SAOR: Single-View Articulated Object Reconstruction
Mehmet Aygün and Oisin Mac Aodha · 2024
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Telling left from right: Identifying geometry-aware semantic correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur, Eric Chen, Varun Jampani, Deqing Sun, and Ming-Hsuan Yang · 2024
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