Establishing semantic correspondence is a challenging task in computer vision, aiming to match keypoints with the same semantic information across different images. We present a non-exhaustive list of papers focused on semantic correspondence. We welcome contributions to enhance this listing—please feel free to submit pull requests with papers in this domain. Finally, please check out our TPAMI 2025 paper "Semantic Correspondence: Unified Benchmarking and a Strong Baseline" for a unified evaluation and a strong baseline. Thank you!
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Semantic Correspondence: Unified Benchmarking and a Strong Baseline
Kaiyan Zhang, Xinghui Li, Jingyi Lu, Kai Han
TPAMI 2025. [Paper] [Project Page] [Code] -
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence
Octave Mariotti, Zhipeng Du, Yash Bhalgat, Oisin Mac Aodha, Hakan Bilen
NeurIPS 2025. [Paper] -
Do It Yourself: Learning Semantic Correspondence from Pseudo-Labels
Olaf Dünkel, Thomas Wimmer, Christian Theobalt, Christian Rupprecht, Adam Kortylewski
ICCV 2025. [Paper] [Project Page] [Code] -
CleanDIFT: Diffusion Features without Noise
Nick Stracke, Stefan Andreas Baumann, Kolja Bauer, Frank Fundel, Björn Ommer
CVPR 2025 Oral. [Paper] [Project Page] [Code] -
SemAlign3D: Semantic Correspondence between RGB-Images through Aligning 3D Object-Class Representations
Krispin Wandel, Hesheng Wang
CVPR 2025. [Paper] [Project Page] [Code] -
Bridging Viewpoint Gaps: Geometric Reasoning Boosts Semantic Correspondence
Qiyang Qian, Hansheng Chen, Masayoshi Tomizuka, Kurt Keutzer, Qianqian Wang, Chenfeng Xu
CVPR 2025. [Paper] [Code] -
Distillation of Diffusion Features for Semantic Correspondence
Frank Fundel, Johannes Schusterbauer, Vincent Tao Hu, Björn Ommer
WACV 2025. [Paper] [Project Page] [Code] -
Towards Robust Semantic Correspondence: A Benchmark and Insights
Wenyue Chong
arXiv preprint 2025. [Paper] -
Unleashing Diffusion Transformers for Visual Correspondence by Modulating Massive Activations
Chaofan Gan, Yuanpeng Tu, Xi Chen, Tieyuan Chen, Yuxi Li, Mehrtash Harandi, Weiyao Lin
arXiv preprint 2025. [Paper]
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DualRC: A Dual-Resolution Learning Framework With Neighbourhood Consensus for Visual Correspondences
Xinghui Li, Kai Han, Shuda Li, Victor Adrian Prisacariu
TPAMI 2024. [Paper] [Project Page] [Code] -
SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matching
Xinghui Li, Jingyi Lu, Kai Han, Victor Adrian Prisacariu
CVPR 2024. [Paper] [Project Page] [Code] -
Telling Left from Right: Identifying Geometry-aware Semantic Correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur, Eric Chen, Varun Jampani, Deqing Sun, Ming-Hsuan Yang
CVPR 2024. [Paper] [Project Page] [Code] -
Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps
Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
CVPR 2024. [Paper] [Code] -
Pixel-level Semantic Correspondence through Layout-aware Representation Learning and Multi-scale Matching Integration
Yixuan Sun, Zhangyue Yin, Haibo Wang, Yan Wang, Xipeng Qiu, Weifeng Ge
CVPR 2024. [Paper] [Code] -
Efficient Semantic Matching with Hypercolumn Correlation
Seungwook Kim, Juhong Min, Minsu Cho
WACV 2024. [Paper] [Project Page] [Code] -
Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
ICLR 2024. [Paper] -
Independently Keypoint Learning for Small Object Semantic Correspondence
Hailong Jin, Huiying Li
arXiv preprint 2024. [Paper] -
LiFT: A Surprisingly Simple Lightweight Feature Transform for Dense ViT Descriptors
Saksham Suri, Matthew Walmer, Kamal Gupta, Abhinav Shrivastava
ECCV 2024. [Paper] [Project Page] [Code] -
Zero-Shot Image Feature Consensus with Deep Functional Maps
Xinle Cheng, Congyue Deng, Adam Harley, Yixin Zhu, Leonidas Guibas
ECCV 2024. [Paper] [Code] -
Match me if you can: Semantic Correspondence Learning with Unpaired Images
Jiwon Kim, Byeongho Heo, Sangdoo Yun, Seungryong Kim, Dongyoon Han
ACCV 2024. [Paper] [Code]
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Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence
Juhong Min, Seungwook Kim, Minsu Cho
TPAMI 2023. [Paper] [Code] -
Cats++: Boosting Cost Aggregation with Convolutions and Transformers
Seokju Cho, Sunghwan Hong, Seungryong Kim
TPAMI 2023. [Paper] [Project Page] [Code] -
Correspondence Transformers with Asymmetric Feature Learning and Matching Flow Super-Resolution
Yixuan Sun, Dongyang Zhao, Zhangyue Yin, Yiwen Huang, Tao Gui, Wenqiang Zhang
CVPR 2023. [Paper] [Code] -
Weakly Supervised Learning of Semantic Correspondence through Cascaded Online Correspondence Refinement
Yiwen Huang, Yixuan Sun, Chenghang Lai, Qing Xu, Xiaomei Wang, Xuli Shen
ICCV 2023. [Paper] [Code] -
ASIC: Aligning Sparse In-The-Wild Image Collections
Kamal Gupta, Varun Jampani, Carlos Esteves, Abhinav Shrivastava, Ameesh Makadia, Noah Snavely, Abhishek Kar
ICCV 2023 Oral. [Paper] [Project Page] [Code] -
Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence
Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell
NeurIPS 2023. [Paper] [Project Page] [Code] -
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, Ming-Hsuan Yang
NeurIPS 2023. [Paper] [Project Page] [Code] -
Unsupervised Semantic Correspondence Using Stable Diffusion
Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi
NeurIPS 2023. [Paper] [Project Page] [Code] -
SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning
Xinghui Li, Kai Han, Xingchen Wan, Victor Adrian Prisacariu
arXiv preprint 2023. [Paper]
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Learning Semantic Correspondence Exploiting an Object-level Prior
Junghyup Lee, Dohyung Kim, Wonkyung Lee, Jean Ponce, Bumsub Ham
TPAMI 2022. [Paper] -
Transformatcher: Match-to-Match Attention for Semantic Correspondence
Seungwook Kim, Juhong Min, Minsu Cho
CVPR 2022. [Paper] [Project Page] [Code] -
GAN-Supervised Dense Visual Alignment
William Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A. Efros, Eli Shechtman
CVPR 2022 Oral. [Paper] [Code] -
CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs
Jiteng Mu, Shalini De Mello, Zhiding Yu, Nuno Vasconcelos, Xiaolong Wang, Jan Kautz, Sifei Liu
CVPR 2022. [Paper] [Project Page] [Code] -
Probabilistic warp consistency for weakly-supervised semantic correspondences
Prune Truong, Martin Danelljan, Fisher Yu, Luc Van Gool
CVPR 2022. [Paper] [Code] -
Semi-supervised learning of semantic correspondence with pseudo-labels
Jiwon Kim, Kwangrok Ryoo, Junyoung Seo, Gyuseong Lee, Daehwan Kim, Hansang Cho, Seungryong Kim
CVPR 2022. [Paper] [Code] -
Cost Aggregation with 4D Convolutional Swin Transformer for Few-shot Segmentation
Sunghwan Hong, Seokju Cho, Jisu Nam, Stephen Lin, Seungryong Kim
ECCV 2022. [Paper] [Project Page] [Code] -
Learning semantic correspondence with sparse annotations
Shuaiyi Huang, Luyu Yang, Bo He, Songyang Zhang, Xuming He, Abhinav Shrivastava
ECCV 2022. [Paper] [Project Page] [Code] -
Demystifying Unsupervised Semantic Correspondence Estimation
Mehmet Aygün, Oisin Mac Aodha
ECCV 2022. [Paper] [Project Page] [Code] -
Deep ViT Features as Dense Visual Descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, Tali Dekel
ECCVW 2022. [Paper] [Project Page] [Code] -
Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence
Sunghwan Hong, Jisu Nam, Seokju Cho, Susung Hong, Sangryul Jeon, Dongbo Min, Seungryong Kim
NeurIPS 2022. [Paper] [Project Page] [Code] -
Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
arXiv preprint 2022. [Paper]
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Convolutional Hough Matching Networks
Juhong Min, Minsu Cho
CVPR 2021. [Paper] [Code] -
Patchmatch-based Neighbourhood Consensus for Semantic Correspondence
Jae Yong Lee, Joseph DeGol, Victor Fragoso, Sudipta N. Sinha
CVPR 2021. [Paper] [Code] -
Cats: Cost Aggregation Transformers for Visual Correspondence
Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, Seungryong Kim
NeurIPS 2021. [Paper] [Code] -
Multi-scale Matching Networks for Semantic Correspondence
Dongyang Zhao, Ziyang Song, Zhenghao Ji, Gangming Zhao, Weifeng Ge, Yizhou Yu
ICCV 2021. [Paper] [Code] -
Warp consistency for unsupervised learning of dense correspondences
Prune Truong, Martin Danelljan, Fisher Yu, Luc Van Gool
ICCV 2021. [Paper] [Code] -
Probabilistic model distillation for semantic correspondence
Xin Li, Deng-Ping Fan, Fan Yang, Ao Luo, Hong Cheng, Zicheng Liu
CVPR 2021. [Paper] [Code] -
Space-Time Correspondence as a Contrastive Random Walk
Allan Jabri, Andrew Owens, Alexei A. Efros
NeurIPS 2021. [Paper] [Project Page] [Code] -
Deep Matching Prior: Test-Time Optimization for Dense Correspondence
Sunghwan Hong, Seungryong Kim
ICCV 2021. [Paper] -
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
Xinlong Wang, Rufeng Zhang, Chunhua Shen, Tao Kong, Lei Li
CVPR 2021. [Paper] [Project Page]
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Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation
Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang, Jia-Bin Huang
TPAMI 2020. [Paper] [Project Page] [Code] -
Discrete-Continuous Transformation Matching for Dense Semantic Correspondence
Seungryong Kim, Dongbo Min, Stephen Lin, Kwanghoon Sohn
TPAMI 2020. [Paper] -
Dual-resolution Correspondence Networks
Xinghui Li, Kai Han, Shuda Li, Victor Adrian Prisacariu
NeurIPS 2020. [Paper] [Project Page] [Code] -
Unsupervised Learning of Dense Visual Representations
Pedro O. O. Pinheiro, Amjad Almahairi, Ryan Benmalek, Florian Golemo, Aaron C. Courville
NeurIPS 2020. [Paper] -
Semantic Correspondence as an Optimal Transport Problem
Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang
CVPR 2020. [Paper] [Code] -
Correspondence Networks with Adaptive Neighbourhood Consensus
Shuda Li, Kai Han, Theo W. Costain, Henry Howard-Jenkins, Victor Adrian Prisacariu
CVPR 2020. [Paper] [Project Page] [Code] -
GLU-Net: Global-local Universal Network for Dense Flow and Correspondences
Prune Truong, Martin Danelljan, Radu Timofte
CVPR 2020 Oral. [Paper] [Code] -
Learning to Compose Hypercolumns for Visual Correspondence
Juhong Min, Jongmin Lee, Jean Ponce, Minsu Cho
ECCV 2020. [Paper] [Project Page] [Code] -
Semantic Correspondence via 2D-3D-2D Cycle
Yang You, Chengkun Li, Yujing Lou, Zhoujun Cheng, Lizhuang Ma, Cewu Lu, Weiming Wang
arXiv preprint 2020. [Paper] [Code]
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FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence
Seungryong Kim, Dongbo Min, Bumsub Ham, Stephen Lin, Kwanghoon Sohn
TPAMI 2019. [Paper] [Project Page] [Code] -
SFNet: Learning Object-aware Semantic Correspondence
Junghyup Lee, Dohyung Kim, Jean Ponce, Bumsub Ham
CVPR 2019. [Paper] [Project Page] [Code] -
Semantic Matching by Weakly Supervised 2D Point Set Registration, Zakaria Laskar, Hamed R. Tavakoli, Juho Kannala
WACV 2019. [Paper] -
Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features
Juhong Min, Jongmin Lee, Jean Ponce, Minsu Cho
ICCV 2019. [Paper] [Project Page] [Code]
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Proposal Flow: Semantic Correspondences from Object Proposals
Bumsub Ham, Minsu Cho, Cordelia Schmid, Jean Ponce
TPAMI 2018. [Paper] [Project Page] [Code] -
Attentive Semantic Alignment with Offset-Aware Correlation Kernels
Paul Hongsuck Seo, Jongmin Lee, Deunsol Jung, Bohyung Han, Minsu Cho
ECCV 2018. [Paper] -
End-to-End Weakly-Supervised Semantic Alignment
Ignacio Rocco, Relja Arandjelović, Josef Sivic
CVPR 2018. [Paper] [Code] -
Recurrent Transformer Networks for Semantic Correspondence
Seungryong Kim, Stephen Lin, Sangryul Jeon, Dongbo Min, Kwanghoon Sohn
NeurIPS 2018. [Paper] [Project Page] [Code] -
PARN: Pyramidal Affine Regression Networks for Dense Semantic Correspondence
Sangryul Jeon, Seungryong Kim, Dongbo Min, Kwanghoon Sohn
ECCV 2018. [Paper] -
Neighbourhood Consensus Networks
Ignacio Rocco, Mircea Cimpoi, Relja Arandjelović, Akihiko Torii, Tomas Pajdla, Josef Sivic
NeurIPS 2018. [Paper] [Project Page] [Code] -
Deep Semantic Matching with Foreground Detection and Cycle-Consistency
Yun-Chun Chen, Po-Hsiang Huang, Li-Yu Yu, Jia-Bin Huang, Ming-Hsuan Yang, Yen-Yu Lin
ACCV 2018. [Paper]
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SCNet: Learning Semantic Correspondence
Kai Han, Rafael S. Rezende, Bumsub Ham, Kwan-Yee K. Wong, Minsu Cho, Cordelia Schmid, Jean Ponce
ICCV 2017. [Paper] [Project Page] [Code] -
FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence
Seungryong Kim, Dongbo Min, Bumsub Ham, Stephen Lin, Kwanghoon Sohn
CVPR 2017. [Paper] [Project Page] [Code] -
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros
ICCV 2017. [Paper] [Project Page] [Code] -
DCTM: Discrete-Continuous Transformation Matching for Semantic Flow
Seungryong Kim, Dongbo Min, Stephen Lin, Kwanghoon Sohn
ICCV 2017. [Paper]
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Proposal Flow
Bumsub Ham, Minsu Cho, Cordelia Schmid, Jean Ponce
CVPR 2016. [Paper] [Project Page] [Code] -
Universal Correspondence Network
Christopher B. Choy, JunYoung Gwak, Silvio Savarese, Manmohan Chandraker
NeurIPS 2016. [Paper] [Code] -
Learning dense correspondence via 3d-guided cycle consistency
Tinghui Zhou, Philipp Krähenbühl, Mathieu Aubry, Qixing Huang, Alexei A. Efros
CVPR 2016. [Paper] -
Unsupervised Object Discovery and Localization in the Wild: Part-Based Matching with Bottom-Up Region Proposals
Minsu Cho, Suha Kwak, Cordelia Schmid, Jean Ponce
CVPR 2015. [Paper] -
Hypercolumns for Object Segmentation and Fine-grained Localization
Bharath Hariharan, Pablo Arbeláez, Ross Girshick, Jitendra Malik
CVPR 2015. [Paper] -
FlowWeb: Joint image set alignment by weaving consistent, pixel-wise correspondences
Tinghui Zhou, Yong Jae Lee, Stella X. Yu, Alexei A. Efros
CVPR 2015. [Paper] [Code] -
DAISY Filter Flow: A Generalized Discrete Approach to Dense Correspondences
Hongsheng Yang, Wen-Yan Lin, Jiangbo Lu
CVPR 2014. [Paper] [Code] -
Deformable Spatial Pyramid Matching for Fast Dense Correspondences
Jaechul Kim, Ce Liu, Fei Sha, Kristen Grauman
CVPR 2013. [Paper] -
Sift Flow: Dense Correspondence Across Scenes and Its Applications
Ce Liu, Jenny Yuen, Antonio Torralba
TPAMI 2011. [Paper] [Code] -
Flexible Object Models for Category-Level 3D Object Recognition
Akash Kushal, Cordelia Schmid, Jean Ponce
CVPR 2007. [Paper] -
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
ICCV 2005. [Paper]