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Given a raw video sequence taken from a freely-moving camera, we study the problem of decomposing the observed 3D scene into a static background and a dynamic foreground containing the objects that move in the video sequence.
The Ecological Approach to Visual Perception
J. J. Gibson · 1986
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A global geometric framework for nonlinear dimensionality reduction
J. B. Tenenbaum, V. de Silva, and J. C. Langford · 2000
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Motion segmentation: A review
Luca Zappella, Xavier Lladó, and Joaquim Salvi · 2008
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Object segmentation by long term analysis of point trajectories
Thomas Brox and Jitendra Malik · 2010
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Dense point trajectories by gpu-accelerated large displacement optical flow
Narayanan Sundaram, Thomas Brox, and Kurt Keutzer · 2010
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Fast object segmentation in unconstrained video
Anestis Papazoglou and Vittorio Ferrari · 2013
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Traditional and recent approaches in background modeling for foreground detection: An overview
Thierry Bouwmans · 2014
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Scene chronology
Kevin Matzen and Noah Snavely · 2014
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Segmentation of moving objects by long term video analysis
P. Ochs, J. Malik, and T. Brox · 2014
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It’s moving! a probabilistic model for causal motion segmentation in moving camera videos
Pia Bideau and Erik Learned-Miller · 2016
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VGG image annotator (VIA)
A. Dutta, A. Gupta, and A. Zissermann · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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Fusionseg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos
Suyog Dutt Jain, Bo Xiong, and Kristen Grauman · 2017
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What uncertainties do we need in Bayesian deep learning for computer vision?
Alex Kendall and Yarin Gal · 2017
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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Learning 3D object categories by looking around them
David Novotný, Diane Larlus, and Andrea Vedaldi · 2017
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Learning motion patterns in videos
Pavel Tokmakov, Karteek Alahari, and Cordelia Schmid · 2017
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Scaling egocentric vision: The epic-kitchens dataset
Dima Damen, Hazel Doughty, Giovanni Maria Farinella, Sanja Fidler, Antonino Furnari, Evangelos Kazakos, Davide Moltisanti, Jonathan Munro, Toby Perrett, Will Price, and Michael Wray · 2018
Cited alongside, same era.
The VIA annotation software for images, audio and video
NeRF++: Analyzing and improving neural radiance fields
Kai Zhang, Gernot Riegler, Noah Snavely, and Vladlen Koltun · 2020
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Animatable neural radiance fields from monocular rgb video
Jianchuan Chen, Ying Zhang, Di Kang, Xuefei Zhe, Linchao Bao, and Huchuan Lu · 2021
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Dynamic view synthesis from dynamic monocular video
Chen Gao, Ayush Saraf, Johannes Kopf, and Jia-Bin Huang · 2021
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Neural scene flow fields for space-time view synthesis of dynamic scenes
Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang · 2021
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NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan T. Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
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Abhishek Dutta and Andrew Zisserman · 2019
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A comprehensive survey of video datasets for background subtraction
Rudrika Kalsotra and Sakshi Arora · 2019
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Zero-shot video object segmentation via attentive graph neural networks
Wenguan Wang, Xiankai Lu, Jianbing Shen, David J Crandall, and Ling Shao · 2019
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Object discovery in videos as foreground motion clustering
Christopher Xie, Yu Xiang, Zaid Harchaoui, and Dieter Fox · 2019
Cited alongside, same era.
Dima Damen, Hazel Doughty, Giovanni Maria Farinella, Antonino Furnari, Jian Ma, Evangelos Kazakos, Davide Moltisanti, Jonathan Munro, Toby Perrett, Will Price, and Michael Wray · 2020
Cited alongside, same era.
A review of motion segmentation: Approaches and major challenges
Jana Mattheus, Hans Grobler, and Adnan M Abu-Mahfouz · 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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Animatable neural radiance fields for human body modeling
Sida Peng, Junting Dong, Qianqian Wang, Shangzhan Zhang, Qing Shuai, Hujun Bao, and Xiaowei Zhou · 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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Decomposing 3d scenes into objects via unsupervised volume segmentation
Karl Stelzner, Kristian Kersting, and Adam R. Kosiorek · 2021
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Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Christoph Lassner, and Christian Theobalt · 2021
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Self-supervised video object segmentation by motion grouping
Charig Yang, Hala Lamdouar, Erika Lu, Andrew Zisserman, and Weidi Xie · 2021
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Learning to segment rigid motions from two frames
Gengshan Yang and Deva Ramanan · 2021
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Star: Self-supervised tracking and reconstruction of rigid objects in motion with neural rendering
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