Chen, Xuelin;
Li, Weiyu;
Cohen-Or, Daniel;
Mitra, Niloy J;
Chen, Baoquan;
(2022)
MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras.
In:
Computer Graphics Forum.
(pp. pp. 147-161).
WILEY
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Abstract
Synthesizing novel views of dynamic humans from stationary monocular cameras is a specialized but desirable setup. This is particularly attractive as it does not require static scenes, controlled environments, or specialized capture hardware. In contrast to techniques that exploit multi-view observations, the problem of modeling a dynamic scene from a single view is significantly more under-constrained and ill-posed. In this paper, we introduce Neural Motion Consensus Flow (MoCo-Flow), a representation that models dynamic humans in stationary monocular cameras using a 4D continuous time-variant function. We learn the proposed representation by optimizing for a dynamic scene that minimizes the total rendering error, over all the observed images. At the heart of our work lies a carefully designed optimization scheme, which includes a dedicated initialization step and is constrained by a motion consensus regularization on the estimated motion flow. We extensively evaluate MoCo-Flow on several datasets that contain human motions of varying complexity, and compare, both qualitatively and quantitatively, to several baselines and ablated variations of our methods, showing the efficacy and merits of the proposed approach. Pretrained model, code, and data will be released for research purposes upon paper acceptance.
| Type: | Proceedings paper |
|---|---|
| Title: | MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras |
| Event: | 43rd Annual Conference of the European-Association-for-Computer-Graphics (EUROGRAPHICS) |
| Location: | Reims, FRANCE |
| Dates: | 25 Apr 2022 - 29 Apr 2022 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/cgf.14465 |
| Publisher version: | https://doi.org/10.1111/cgf.14465 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Computer Science, Software Engineering, Computer Science, CCS Concepts, center dot Computing methodologies -> Shape modeling, Rendering, CAPTURE |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10159069 |
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