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Recent advances in large-scale pretraining have yielded visual foundation models with strong capabilities.
Second-order isomorphism of internal representations: Shapes of states
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Jan J Koenderink and Andrea J Van Doorn · 1979
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Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
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Shape matching and object recognition using low distortion correspondences
Alexander C Berg, Tamara L Berg, and Jitendra Malik · 2005
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Visual discrimination of local surface structure: Slant, tilt, and curvedness
J Farley Norman, James T Todd, Hideko F Norman, Anna Marie Clayton, and T Ryan McBride · 2006
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Beyond core knowledge: Natural geometry
Elizabeth Spelke, Sang Ah Lee, and Véronique Izard · 2010
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Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
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Return of the devil in the details: delving deep into convolutional nets
K Chatfield, K Simonyan, A Vedaldi, and A Zisserman · 2014
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Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
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Discriminatively trained dense surface normal estimation
L’ubor Ladickỳ, Bernhard Zeisl, and Marc Pollefeys · 2014
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Beyond pascal: A benchmark for 3d object detection in the wild
Yu Xiang, Roozbeh Mottaghi, and Silvio Savarese · 2014
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Single image 3D without a single 3D image
David F. Fouhey, Wajahat Hussain, Abhinav Gupta, and Martial Hebert · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2015
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Factoring Scenes into 3D Structure and Style
David Fouhey · 2016
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SGDR: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Megadepth: Learning single-view depth prediction from internet photos
Zhengqi Li and Noah Snavely · 2018
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Scaling and benchmarking self-supervised visual representation learning
Priya Goyal, Dhruv Mahajan, Abhinav Gupta, and Ishan Misra · 2019
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Do better imagenet models transfer better?
Simon Kornblith, Jonathon Shlens, and Quoc V Le · 2019
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Spair-71k: A large-scale benchmark for semantic correspondence
Juhong Min, Jongmin Lee, Jean Ponce, and Minsu Cho · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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What do single-view 3d reconstruction networks learn?
Maxim Tatarchenko, Stephan R Richter, René Ranftl, Zhuwen Li, Vladlen Koltun, and Thomas Brox · 2019
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Pytorch image models
Ross Wightman · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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On the variance of the adaptive learning rate and beyond
Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, and Jiawei Han · 2020
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
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Superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
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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Zoedepth: Zero-shot transfer by combining relative and metric depth
Shariq Farooq Bhat, Reiner Birkl, Diana Wofk, Peter Wonka, and Matthias Müller · 2023
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Stylegan knows normal, depth, albedo, and more
Anand Bhattad, Daniel McKee, Derek Hoiem, and DA Forsyth · 2023
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Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, Aaron Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Patrick Murphy, William T Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan · 2023
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Beyond surface statistics: Scene representations in a latent diffusion model
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Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 2021
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Estimating and exploiting the aleatoric uncertainty in surface normal estimation
Gwangbin Bae, Ignas Budvytis, and Roberto Cipolla · 2021
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Adabins: Depth estimation using adaptive bins
Shariq Farooq Bhat, Ibraheem Alhashim, and Peter Wonka · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Bootstrap Your Own Correspondences
Mohamed El Banani and Justin Johnson · 2021
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UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering
Mohamed El Banani, Luya Gao, and Justin Johnson · 2021
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OpenCLIP, 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 2021
Cited alongside, same era.
Yida Chen, Fernanda Viégas, and Martin Wattenberg · 2023
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Vision transformers need registers
Timothée Darcet, Maxime Oquab, Julien Mairal, and Piotr Bojanowski · 2023
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Generative models: What do they know? do they know things? let’s find out!
Xiaodan Du, Nicholas Kolkin, Greg Shakhnarovich, and Anand Bhattad · 2023
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Learning Visual Representations via Language-Guided Sampling
Mohamed El Banani, Karan Desai, and Justin Johnson · 2023
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Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks
Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, and Tom Goldstein · 2023
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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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Navi: Category-agnostic image collections with high-quality 3d shape and pose annotations
Varun Jampani, Kevis-Kokitsi Maninis, Andreas Engelhardt, Arjun Karpur, Karen Truong, Kyle Sargent, Stefan Popov, André Araujo, Ricardo Martin-Brualla, Kaushal Patel, Daniel Vlasic, Vittorio Ferrari, Ameesh Makadia, Ce Liu, Yuanzhen Li, and Howard Zhou · 2023
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Repurposing diffusion-based image generators for monocular depth estimation
Bingxin Ke, Anton Obukhov, Shengyu Huang, Nando Metzger, Rodrigo Caye Daudt, and Konrad Schindler · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Your diffusion model is secretly a zero-shot classifier
Alexander C. Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak · 2023
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Zero-1-to-3: Zero-shot one image to 3d object
Ruoshi Liu, Rundi Wu, Basile Van Hoorick, Pavel Tokmakov, Sergey Zakharov, and Carl Vondrick · 2023
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Diffusion hyperfeatures: Searching through time and space for semantic correspondence
Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, and Trevor Darrell · 2023
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DINOv2: Learning Robust Visual Features without Supervision, 2023
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2023
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idisc: Internal discretization for monocular depth estimation
Luigi Piccinelli, Christos Sakaridis, and Fisher Yu · 2023
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Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, and Bernard Ghanem · 2023
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Dreambooth3d: Subject-driven text-to-3d generation
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan Barron, Yuanzhen Li, and Varun Jampani · 2023
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Shadows don’t lie and lines can’t bend! generative models don’t know projective geometry…for now
Ayush Sarkar, Hanlin Mai, Amitabh Mahapatra, Svetlana Lazebnik, David Forsyth, and Anand Bhattad · 2023
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Mvdream: Multi-view diffusion for 3d generation
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 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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Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A Yeh, and Greg Shakhnarovich · 2023
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Convnext v2: Co-designing and scaling convnets with masked autoencoders
Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, and Saining Xie · 2023
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Metric3d: Towards zero-shot metric 3d prediction from a single image
Wei Yin, Chi Zhang, Hao Chen, Zhipeng Cai, Gang Yu, Kaixuan Wang, Xiaozhi Chen, and Chunhua Shen · 2023
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Sigmoid loss for language image pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, and Lucas Beyer · 2023
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What does stable diffusion know about the 3d scene?, 2023
Guanqi Zhan, Chuanxia Zheng, Weidi Xie, and Andrew Zisserman · 2023
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Unleashing text-to-image diffusion models for visual perception
Wenliang Zhao, Yongming Rao, Zuyan Liu, Benlin Liu, Jie Zhou, and Jiwen Lu · 2023
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Localization vs. semantics: Visual representations in unimodal and multimodal models
Zhuowan Li, Cihang Xie, Benjamin Van Durme, and Alan Yuille · 2024
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