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Finding correspondences between images is a fundamental problem in computer vision.
Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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Surf: Speeded up robust features
H. Bay, T. Tuytelaars, and L. Van Gool · 2006
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
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Building rome in a day
S. Agarwal, Y. Furukawa, N. Snavely, I. Simon, B. Curless, S. M. Seitz, and R. Szeliski · 2011
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The caltech-ucsd birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Unsupervised co-segmentation through region matching
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Towards understanding action recognition
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U-net: Convolutional networks for biomedical image segmentation
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Proposal flow
B. Ham, M. Cho, C. Schmid, and J. Ponce · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
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Structure-from-motion revisited
J. L. Schönberger and J.-M. Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
J. L. Schönberger, E. Zheng, M. Pollefeys, and J.-M. Frahm · 2016
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Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors
V. Balntas, K. Lenc, A. Vedaldi, and K. Mikolajczyk · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
J. Carreira and A. Zisserman · 2017
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Scnet: Learning semantic correspondence
K. Han, R. S. Rezende, B. Ham, K.-Y. K. Wong, M. Cho, C. Schmid, and J. Ponce · 2017
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A survey of structure from motion
O. Özyeşil, V. Voroninski, R. Basri, and A. Singer · 2017
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Object-part attention model for fine-grained image classification
Y. Peng, X. He, and J. Zhao · 2017
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The 2017 davis challenge on video object segmentation
J. Pont-Tuset, F. Perazzi, S. Caelles, P. Arbeláez, A. Sorkine-Hornung, and L. Van Gool · 2017
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Convolutional neural network architecture for geometric matching
I. Rocco, R. Arandjelovic, and J. Sivic · 2017
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Neural best-buddies: Sparse cross-domain correspondence
K. Aberman, J. Liao, M. Shi, D. Lischinski, B. Chen, and D. Cohen-Or · 2018
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Superpoint: Self-supervised interest point detection and description
D. DeTone, T. Malisiewicz, and A. Rabinovich · 2018
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From lifestyle vlogs to everyday interactions
D. F. Fouhey, W.-c. Kuo, A. A. Efros, and J. Malik · 2018
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Lf-net: Learning local features from images
Y. Ono, E. Trulls, P. Fua, and K. M. Yi · 2018
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End-to-end weakly-supervised semantic alignment
I. Rocco, R. Arandjelović, and J. Sivic · 2018
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Neighbourhood consensus networks
I. Rocco, M. Cimpoi, R. Arandjelović, A. Torii, T. Pajdla, and J. Sivic · 2018
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Attentive semantic alignment with offset-aware correlation kernels
P. H. Seo, J. Lee, D. Jung, B. Han, and M. Cho · 2018
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Long-term tracking in the wild: A benchmark
J. Valmadre, L. Bertinetto, J. F. Henriques, R. Tao, A. Vedaldi, A. W. Smeulders, P. H. Torr, and E. Gavves · 2018
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Tracking emerges by colorizing videos
C. Vondrick, A. Shrivastava, A. Fathi, S. Guadarrama, and K. Murphy · 2018
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Unsupervised feature learning via non-parametric instance-level discrimination
Z. Wu, Y. Xiong, S. Yu, and D. Lin · 2018
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Youtube-vos: A large-scale video object segmentation benchmark
N. Xu, L. Yang, Y. Fan, D. Yue, Y. Liang, J. Yang, and T. Huang · 2018
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D2-net: A trainable cnn for joint detection and description of local features
M. Dusmanu, I. Rocco, T. Pajdla, M. Pollefeys, J. Sivic, A. Torii, and T. Sattler · 2019
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Self-supervised learning for video correspondence flow
Z. Lai and W. Xie · 2019
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Sfnet: Learning object-aware semantic correspondence
J. Lee, D. Kim, J. Ponce, and B. Ham · 2019
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Deep object co-segmentation
W. Li, O. Hosseini Jafari, and C. Rother · 2019
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Joint-task self-supervised learning for temporal correspondence
X. Li, S. Liu, S. De Mello, X. Wang, J. Kautz, and M.-H. Yang · 2019
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Contextdesc: Local descriptor augmentation with cross-modality context
Z. Luo, T. Shen, L. Zhou, J. Zhang, Y. Yao, S. Li, T. Fang, and L. Quan · 2019
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Spair-71k: A large-scale benchmark for semantic correspondence
J. Min, J. Lee, J. Ponce, and M. Cho · 2019
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R2d2: repeatable and reliable detector and descriptor
J. Revaud, P. Weinzaepfel, C. De Souza, N. Pion, G. Csurka, Y. Cabon, and M. Humenberger · 2019
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Probabilistic model distillation for semantic correspondence
X. Li, D.-P. Fan, F. Yang, A. Luo, H. Cheng, and Z. Liu · 2021
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Unsupervised part segmentation through disentangling appearance and shape
S. Liu, L. Zhang, X. Yang, H. Su, and J. Zhu · 2021
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Sdedit: Guided image synthesis and editing with stochastic differential equations
C. Meng, Y. He, Y. Song, J. Song, J. Wu, J.-Y. Zhu, and S. Ermon · 2021
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Convolutional hough matching networks
J. Min and M. Cho · 2021
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High-resolution image synthesis with latent diffusion models, 2021
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2021
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Warp consistency for unsupervised learning of dense correspondences
P. Truong, M. Danelljan, F. Yu, and L. Van Gool · 2021
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Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
Cited alongside, same era.
Learning correspondence from the cycle-consistency of time
X. Wang, A. Jabri, and A. A. Efros · 2019
Cited alongside, same era.
Concept learners for few-shot learning
K. Cao, M. Brbic, and J. Leskovec · 2020
Cited alongside, same era.
A simple framework for contrastive learning of visual representations
T. Chen, S. Kornblith, M. Norouzi, and G. Hinton · 2020
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, et al · 2020
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Generative adversarial networks
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2020
Cited alongside, same era.
Watching the world go by: Representation learning from unlabeled videos
D. Gordon, K. Ehsani, D. Fox, and A. Farhadi · 2020
Cited alongside, same era.
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Rethinking self-supervised correspondence learning: A video frame-level similarity perspective
J. Xu and X. Wang · 2021
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Datasetgan: Efficient labeled data factory with minimal human effort
Y. Zhang, H. Ling, J. Gao, K. Yin, J.-F. Lafleche, A. Barriuso, A. Torralba, and S. Fidler · 2021
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Multi-scale matching networks for semantic correspondence
D. Zhao, Z. Song, Z. Ji, G. Zhao, W. Ge, and Y. Yu · 2021
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Transfill: Reference-guided image inpainting by merging multiple color and spatial transformations
Y. Zhou, C. Barnes, E. Shechtman, and S. Amirghodsi · 2021
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Instructpix2pix: Learning to follow image editing instructions
T. Brooks, A. Holynski, and A. A. Efros · 2022
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Aiatrack: Attention in attention for transformer visual tracking
S. Gao, C. Zhou, C. Ma, X. Wang, and J. Yuan · 2022
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Unsupervised semantic segmentation by distilling feature correspondences
M. Hamilton, Z. Zhang, B. Hariharan, N. Snavely, and W. T. Freeman · 2022
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Prompt-to-prompt image editing with cross attention control
A. Hertz, R. Mokady, J. Tenenbaum, K. Aberman, Y. Pritch, and D. Cohen-Or · 2022
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Classifier-free diffusion guidance
J. Ho and T. Salimans · 2022
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Semantic-aware fine-grained correspondence
Y. Hu, R. Wang, K. Zhang, and Y. Gao · 2022
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Learning semantic correspondence with sparse annotations
S. Huang, L. Yang, B. He, S. Zhang, X. He, and A. Shrivastava · 2022
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Elucidating the design space of diffusion-based generative models
T. Karras, M. Aittala, T. Aila, and S. Laine · 2022
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Transformatcher: Match-to-match attention for semantic correspondence
S. Kim, J. Min, and M. Cho · 2022
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Coordgan: Self-supervised dense correspondences emerge from gans
J. Mu, S. De Mello, Z. Yu, N. Vasconcelos, X. Wang, J. Kautz, and S. Liu · 2022
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Gan-supervised dense visual alignment
W. Peebles, J.-Y. Zhu, R. Zhang, A. Torralba, A. Efros, and E. Shechtman · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
C. Schuhmann, R. Beaumont, R. Vencu, C. Gordon, R. Wightman, M. Cherti, T. Coombes, A. Katta, C. Mullis, M. Wortsman, et al · 2022
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Probabilistic warp consistency for weakly-supervised semantic correspondences
P. Truong, M. Danelljan, F. Yu, and L. Van Gool · 2022
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Splicing vit features for semantic appearance transfer
N. Tumanyan, O. Bar-Tal, S. Bagon, and T. Dekel · 2022
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Plug-and-play diffusion features for text-driven image-to-image translation
N. Tumanyan, M. Geyer, S. Bagon, and T. Dekel · 2022
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Towards grand unification of object tracking
B. Yan, Y. Jiang, P. Sun, D. Wang, Z. Yuan, P. Luo, and H. Lu · 2022
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Asic: Aligning sparse in-the-wild image collections
K. Gupta, V. Jampani, C. Esteves, A. Shrivastava, A. Makadia, N. Snavely, and A. Kar · 2023
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Neural congealing: Aligning images to a joint semantic atlas
D. Ofri-Amar, M. Geyer, Y. Kasten, and T. Dekel · 2023
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Zero-shot image-to-image translation
G. Parmar, K. K. Singh, R. Zhang, Y. Li, J. Lu, and J.-Y. Zhu · 2023
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Realfill: Reference-driven generation for authentic image completion
L. Tang, N. Ruiz, Q. Chu, Y. Li, A. Holynski, D. E. Jacobs, B. Hariharan, Y. Pritch, N. Wadhwa, K. Aberman, et al · 2023
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Tracking everything everywhere all at once
Q. Wang, Y.-Y. Chang, R. Cai, Z. Li, B. Hariharan, A. Holynski, and N. Snavely · 2023
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Open-vocabulary panoptic segmentation with text-to-image diffusion models
J. Xu, S. Liu, A. Vahdat, W. Byeon, X. Wang, and S. De Mello · 2023
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Videodoodles: Hand-drawn animations on videos with scene-aware canvases
E. Yu, K. Blackburn-Matzen, C. Nguyen, O. Wang, R. Habib Kazi, and A. Bousseau · 2023
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Unleashing text-to-image diffusion models for visual perception
W. Zhao, Y. Rao, Z. Liu, B. Liu, J. Zhou, and J. Lu · 2023
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