Fetching the paper…
Reading the bibliography…
We present a method for joint alignment of sparse in-the-wild image collections of an object category.
Who belongs in the family
Robert L Thorndike · 1953
Earlier work this paper cites.
Splines minimizing rotation-invariant semi-norms in sobolev spaces
Jean Duchon · 1977
Earlier work this paper cites.
Determining optical flow
Berthold KP Horn and Brian G Schunck · 1981
Earlier work this paper cites.
An iterative image registration technique with an application to stereo vision
Bruce D Lucas, Takeo Kanade, et al · 1981
Earlier work this paper cites.
Recognition-by-components: a theory of human image understanding
Irving Biederman · 1987
Earlier work this paper cites.
Detection and tracking of point
Carlo Tomasi and Takeo Kanade · 1991
Earlier work this paper cites.
Robust estimation of a location parameter
Peter J Huber · 1992
Earlier work this paper cites.
A framework for the robust estimation of optical flow
Michael J Black and Padmanabhan Anandan · 1993
Earlier work this paper cites.
The computation of optical flow
Steven S. Beauchemin and John L. Barron · 1995
Earlier work this paper cites.
Multi-feature hierarchical template matching using distance transforms
Dariu M Gavrila · 1998
Earlier work this paper cites.
Probabilistic methods for finding people
Sergey Ioffe and David A. Forsyth · 2001
Earlier work this paper cites.
Sift-the scale invariant feature transform
G Lowe · 2004
Earlier work this paper cites.
” grabcut” interactive foreground extraction using iterated graph cuts
Carsten Rother, Vladimir Kolmogorov, and Andrew Blake · 2004
Earlier work this paper cites.
Data driven image models through continuous joint alignment
Erik G Learned-Miller · 2005
Earlier work this paper cites.
Image deformation using moving least squares
Scott Schaefer, Travis McPhail, and Joe Warren · 2006
Earlier work this paper cites.
Unsupervised joint alignment of complex images
Gary B Huang, Vidit Jain, and Erik Learned-Miller · 2007
Earlier work this paper cites.
Image alignment and stitching: A tutorial
Richard Szeliski et al · 2007
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Building rome on a cloudless day
Jan-Michael Frahm, Pierre Fite-Georgel, David Gallup, Tim Johnson, Rahul Raguram, Changchang Wu, Yi-Hung Jen, Enrique Dunn, Brian Clipp, Svetlana Lazebnik, et al · 2010
Earlier work this paper cites.
Sift flow: Dense correspondence across scenes and its applications
Ce Liu, Jenny Yuen, and Antonio Torralba · 2010
Earlier work this paper cites.
Building rome in a day
Sameer Agarwal, Yasutaka Furukawa, Noah Snavely, Ian Simon, Brian Curless, Steven M Seitz, and Richard Szeliski · 2011
Earlier work this paper cites.
The Caltech-UCSD Birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Earlier work this paper cites.
Learning to align from scratch
Gary Huang, Marwan Mattar, Honglak Lee, and Erik Learned-Miller · 2012
Earlier work this paper cites.
Articulated human detection with flexible mixtures of parts
Yi Yang and Deva Ramanan · 2012
Earlier work this paper cites.
Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Universal correspondence network
Christopher B Choy, JunYoung Gwak, Silvio Savarese, and Manmohan Chandraker · 2016
Earlier work this paper cites.
Proposal flow
Bumsub Ham, Minsu Cho, Cordelia Schmid, and Jean Ponce · 2016
Earlier work this paper cites.
Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
Cited alongside, same era.
Fcss: Fully convolutional self-similarity for dense semantic correspondence
Seungryong Kim, Dongbo Min, Bumsub Ham, Sangryul Jeon, Stephen Lin, and Kwanghoon Sohn · 2017
Cited alongside, same era.
Convolutional neural network architecture for geometric matching
Ignacio Rocco, Relja Arandjelovic, and Josef Sivic · 2017
Cited alongside, same era.
Unsupervised learning of object frames by dense equivariant image labelling
James Thewlis, Hakan Bilen, and Andrea Vedaldi · 2017
Cited alongside, same era.
Neural best-buddies: Sparse cross-domain correspondence
Kfir Aberman, Jing Liao, Mingyi Shi, Dani Lischinski, Baoquan Chen, and Daniel Cohen-Or · 2018
Cited alongside, same era.
Superpoint: Self-supervised interest point detection and description
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2018
Correspondence networks with adaptive neighbourhood consensus
Shuda Li, Kai Han, Theo W Costain, Henry Howard-Jenkins, and Victor Prisacariu · 2020
Later among the works it cites.
Semantic correspondence as an optimal transport problem
Yanbin Liu, Linchao Zhu, Makoto Yamada, and Yi Yang · 2020
Later among the works it cites.
Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
Later among the works it cites.
Superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
Later among the works it cites.
Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 2021
Later among the works it cites.
Cats: Cost aggregation transformers for visual correspondence
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Parn: Pyramidal affine regression networks for dense semantic correspondence
Sangryul Jeon, Seungryong Kim, Dongbo Min, and Kwanghoon Sohn · 2018
Cited alongside, same era.
Learning category-specific mesh reconstruction from image collections
Angjoo Kanazawa, Shubham Tulsiani, Alexei A. Efros, and Jitendra Malik · 2018
Cited alongside, same era.
Self-supervised learning of geometrically stable features through probabilistic introspection
David Novotny, Samuel Albanie, Diane Larlus, and Andrea Vedaldi · 2018
Cited alongside, same era.
End-to-end weakly-supervised semantic alignment
Ignacio Rocco, Relja Arandjelović, and Josef Sivic · 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.
Attentive semantic alignment with offset-aware correlation kernels
Paul Hongsuck Seo, Jongmin Lee, Deunsol Jung, Bohyung Han, and Minsu Cho · 2018
Cited alongside, same era.
Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, and Seungryong Kim · 2021
Later among the works it cites.
Unsupervised part discovery from contrastive reconstruction
Subhabrata Choudhury, Iro Laina, Christian Rupprecht, and Andrea Vedaldi · 2021
Later among the works it cites.
Deep matching prior: Test-time optimization for dense correspondence
Sunghwan Hong and Seungryong Kim · 2021
Later among the works it cites.
Pyramidal semantic correspondence networks
Sangryul Jeon, Seungryong Kim, Dongbo Min, and Kwanghoon Sohn · 2021
Later among the works it cites.
COTR: Correspondence transformer for matching across images
Wei Jiang, Eduard Trulls, Jan Hosang, Andrea Tagliasacchi, and Kwang Moo Yi · 2021
Later among the works it cites.
Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
Later among the works it cites.
Layered neural atlases for consistent video editing
Yoni Kasten, Dolev Ofri, Oliver Wang, and Tali Dekel · 2021
Later among the works it cites.
Patchmatch-based neighborhood consensus for semantic correspondence
Jae Yong Lee, Joseph DeGol, Victor Fragoso, and Sudipta N Sinha · 2021
Later among the works it cites.
Probabilistic model distillation for semantic correspondence
Xin Li, Deng-Ping Fan, Fan Yang, Ao Luo, Hong Cheng, and Zicheng Liu · 2021
Later among the works it cites.
Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
Later among the works it cites.
Convolutional hough matching networks
Juhong Min and Minsu Cho · 2021
Later among the works it cites.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Later among the works it cites.
Loftr: Detector-free local feature matching with transformers
Jiaming Sun, Zehong Shen, Yuang Wang, Hujun Bao, and Xiaowei Zhou · 2021
Later among the works it cites.
Warp consistency for unsupervised learning of dense correspondences
Prune Truong, Martin Danelljan, Fisher Yu, and Luc Van Gool · 2021
Later among the works it cites.
Ners: Neural reflectance surfaces for sparse-view 3d reconstruction in the wild
Jason Zhang, Gengshan Yang, Shubham Tulsiani, and Deva Ramanan · 2021
Later among the works it cites.
Multi-scale matching networks for semantic correspondence
Dongyang Zhao, Ziyang Song, Zhenghao Ji, Gangming Zhao, Weifeng Ge, and Yizhou Yu · 2021
Later among the works it cites.
Demystifying unsupervised semantic correspondence estimation
Mehmet Aygün and Oisin Mac Aodha · 2022
Later among the works it cites.
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Mark Boss, Andreas Engelhardt, Abhishek Kar, Yuanzhen Li, Deqing Sun, Jonathan T. Barron, Hendrik P.A. Lensch, and Varun Jampani · 2022
Later among the works it cites.
Learning semantic correspondence with sparse annotations
Shuaiyi Huang, Luyu Yang, Bo He, Songyang Zhang, Xuming He, and Abhinav Shrivastava · 2022
Later among the works it cites.
Coordgan: Self-supervised dense correspondences emerge from gans
Jiteng Mu, Shalini De Mello, Zhiding Yu, Nuno Vasconcelos, Xiaolong Wang, Jan Kautz, and Sifei Liu · 2022
Later among the works it cites.
Gan-supervised dense visual alignment
William Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A Efros, and Eli Shechtman · 2022
Later among the works it cites.
Lassie: Learning articulated shapes from sparse image ensemble via 3d part discovery
Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, and Varun Jampani · 2022
Later among the works it cites.
Neural congealing: Aligning images to a joint semantic atlas
Dolev Ofri-Amar, Michal Geyer, Yoni Kasten, and Tali Dekel · 2023
Closest in time.