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View-predictive generative models provide strong priors for lifting object-centric images and videos into 3D and 4D through rendering and score distillation objectives.
The 2017 davis challenge on video object segmentation
Jordi Pont-Tuset, Federico Perazzi, Sergi Caelles, Pablo Arbeláez, Alex Sorkine-Hornung, and Luc Van Gool · 2017
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Sfv: Reinforcement learning of physical skills from videos
Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, and Sergey Levine · 2018
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Youtube-vos: Sequence-to-sequence video object segmentation
Ning Xu, Linjie Yang, Yuchen Fan, Jianchao Yang, Dingcheng Yue, Yuchen Liang, Brian Price, Scott Cohen, and Thomas Huang · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Learnable gated temporal shift module for deep video inpainting
Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee, and Winston Hsu · 2019
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Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 2019
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Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
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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 · 2020
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Nerfies: Deformable neural radiance fields
Keunhong Park, Utkarsh Sinha, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Steven M Seitz, and Ricardo Martin-Brualla · 2021
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Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields
Keunhong Park, Utkarsh Sinha, Peter Hedman, Jonathan T. Barron, Sofien Bouaziz, Dan B Goldman, Ricardo Martin-Brualla, and Steven M. Seitz · 2021
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D-nerf: Neural radiance fields for dynamic scenes
Albert Pumarola, Enric Corona, Gerard Pons-Moll, and Francesc Moreno-Noguer · 2021
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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
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model
Ho Kei Cheng and Alexander G Schwing · 2022
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Tap-vid: A benchmark for tracking any point in a video
Carl Doersch, Ankush Gupta, Larisa Markeeva, Adria Recasens, Lucas Smaira, Yusuf Aytar, Joao Carreira, Andrew Zisserman, and Yi Yang · 2022
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Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, et al · 2022
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Inferring articulated rigid body dynamics from rgbd video
Eric Heiden, Ziang Liu, Vibhav Vineet, Erwin Coumans, and Gaurav S Sukhatme · 2022
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Neural 3d video synthesis from multi-view video
Tianye Li, Mira Slavcheva, Michael Zollhoefer, Simon Green, Christoph Lassner, Changil Kim, Tanner Schmidt, Steven Lovegrove, Michael Goesele, Richard Newcombe, et al · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
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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 · 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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Resolution-robust large mask inpainting with fourier convolutions
Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, and Victor Lempitsky · 2022
Cited alongside, same era.
Gmflow: Learning optical flow via global matching
Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, and Dacheng Tao · 2022
Cited alongside, same era.
4d-fy: Text-to-4d generation using hybrid score distillation sampling
Sherwin Bahmani, Ivan Skorokhodov, Victor Rong, Gordon Wetzstein, Leonidas Guibas, Peter Wonka, Sergey Tulyakov, Jeong Joon Park, Andrea Tagliasacchi, and David B Lindell · 2023
Cited alongside, same era.
Nope-nerf: Optimising neural radiance field with no pose prior
Wenjing Bian, Zirui Wang, Kejie Li, Jia-Wang Bian, and Victor Adrian Prisacariu · 2023
Cited alongside, same era.
Flowibr: Leveraging pre-training for efficient neural image-based rendering of dynamic scenes
Marcel Büsching, Josef Bengtson, David Nilsson, and Mårten Björkman · 2023
Text-to-4d dynamic scene generation
Uriel Singer, Shelly Sheynin, Adam Polyak, Oron Ashual, Iurii Makarov, Filippos Kokkinos, Naman Goyal, Andrea Vedaldi, Devi Parikh, Justin Johnson, et al · 2023
Later among the works it cites.
Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation
Jay Zhangjie Wu, Yixiao Ge, Xintao Wang, Stan Weixian Lei, Yuchao Gu, Yufei Shi, Wynne Hsu, Ying Shan, Xiaohu Qie, and Mike Zheng Shou · 2023
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Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction
Ziyi Yang, Xinyu Gao, Wen Zhou, Shaohui Jiao, Yuqing Zhang, and Xiaogang Jin · 2023
Later among the works it cites.
Decoupling human and camera motion from videos in the wild
Vickie Ye, Georgios Pavlakos, Jitendra Malik, and Angjoo Kanazawa · 2023
Later among the works it cites.
4dgen: Grounded 4d content generation with spatial-temporal consistency
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Cited alongside, same era.
Hexplane: A fast representation for dynamic scenes
Ang Cao and Justin Johnson · 2023
Cited alongside, same era.
Pix2video: Video editing using image diffusion
Duygu Ceylan, Chun-Hao P Huang, and Niloy J Mitra · 2023
Cited alongside, same era.
Objaverse: A universe of annotated 3d objects
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi · 2023
Cited alongside, same era.
K-planes: Explicit radiance fields in space, time, and appearance
Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbæk Warburg, Benjamin Recht, and Angjoo Kanazawa · 2023
Cited alongside, same era.
Cotracker: It is better to track together
Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, and Christian Rupprecht · 2023
Cited alongside, same era.
Segment anything in high quality
Lei Ke, Mingqiao Ye, Martin Danelljan, Yifan Liu, Yu-Wing Tai, Chi-Keung Tang, and Fisher Yu · 2023
Cited alongside, same era.
3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
Cited alongside, same era.
Yuyang Yin, Dejia Xu, Zhangyang Wang, Yao Zhao, and Yunchao Wei · 2023
Later among the works it cites.
Animate124: Animating one image to 4d dynamic scene
Yuyang Zhao, Zhiwen Yan, Enze Xie, Lanqing Hong, Zhenguo Li, and Gim Hee Lee · 2023
Later among the works it cites.
Pointodyssey: A large-scale synthetic dataset for long-term point tracking
Yang Zheng, Adam W Harley, Bokui Shen, Gordon Wetzstein, and Leonidas J Guibas · 2023
Later among the works it cites.
A unified approach for text-and image-guided 4d scene generation
Yufeng Zheng, Xueting Li, Koki Nagano, Sifei Liu, Otmar Hilliges, and Shalini De Mello · 2023
Later among the works it cites.
Tc4d: Trajectory-conditioned text-to-4d generation
Sherwin Bahmani, Xian Liu, Yifan Wang, Ivan Skorokhodov, Victor Rong, Ziwei Liu, Xihui Liu, Jeong Joon Park, Sergey Tulyakov, Gordon Wetzstein, et al · 2024
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Zero-shot open-vocabulary tracking with large pre-trained models
Wen-Hsuan Chu, Adam W Harley, Pavel Tokmakov, Achal Dave, Leonidas Guibas, and Katerina Fragkiadaki · 2024
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Gaussianflow: Splatting gaussian dynamics for 4d content creation
Quankai Gao, Qiangeng Xu, Zhe Cao, Ben Mildenhall, Wenchao Ma, Le Chen, Danhang Tang, and Ulrich Neumann · 2024
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Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis
Jonathon Luiten, Georgios Kopanas, Bastian Leibe, and Deva Ramanan · 2024
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Fast dynamic 3d object generation from a single-view video
Zijie Pan, Zeyu Yang, Xiatian Zhu, and Li Zhang · 2024
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Grounded sam: Assembling open-world models for diverse visual tasks
Tianhe Ren, Shilong Liu, Ailing Zeng, Jing Lin, Kunchang Li, He Cao, Jiayu Chen, Xinyu Huang, Yukang Chen, Feng Yan, et al · 2024
Closest in time.
Dreamgaussian: Generative gaussian splatting for efficient 3d content creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, and Gang Zeng · 2024
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Dust3r: Geometric 3d vision made easy
Shuzhe Wang, Vincent Leroy, Yohann Cabon, Boris Chidlovskii, and Jerome Revaud · 2024
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4d gaussian splatting for real-time dynamic scene rendering
Guanjun Wu, Taoran Yi, Jiemin Fang, Lingxi Xie, Xiaopeng Zhang, Wei Wei, Wenyu Liu, Qi Tian, and Xinggang Wang · 2024
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Comp4d: Llm-guided compositional 4d scene generation
Dejia Xu, Hanwen Liang, Neel P Bhatt, Hezhen Hu, Hanxue Liang, Konstantinos N Plataniotis, and Zhangyang Wang · 2024
Closest in time.
Depth anything: Unleashing the power of large-scale unlabeled data
Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
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Beyond skeletons: Integrative latent mapping for coherent 4d sequence generation
Qitong Yang, Mingtao Feng, Zijie Wu, Shijie Sun, Weisheng Dong, Yaonan Wang, and Ajmal Mian · 2024
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Stag4d: Spatial-temporal anchored generative 4d gaussians
Yifei Zeng, Yanqin Jiang, Siyu Zhu, Yuanxun Lu, Youtian Lin, Hao Zhu, Weiming Hu, Xun Cao, and Yao Yao · 2024
Closest in time.