TRACE: 5D Temporal Regression of Avatars with Dynamic Cameras in 3D Environments
Yu Sun, Qian Bao, Wu Liu, Tao Mei, Michael J. Black
2023年份
53顶会引用
摘要
Figure 1. 5D temporal reconstruction of multiple 3D people in global coordinates with a dynamic camera. We introduce TRACE, a monocular one-stage method with a holistic 5D representation that enables the network to explicitly reason about human motion across time. Unlike previous methods [45,46] (b) that regress all 3D people from each frame in camera coordinates, TRACE (c) tracks the subjects (a) presented in the first frame through time and recovers their global trajectories in global coordinates in one shot.
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引用它的顶会 Paper53
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- AiOS: All-in-One-Stage Expressive Human Pose and Shape EstimationQingping Sun, Yanjun Wang, Ailing Zeng, Wanqi Yin 等CVPR 2024 · 被引用 20 次
- GENMO: A GENeralist Model for Human MOtionJiefeng Li, Jinkun Cao, Haotian Zhang, Davis Rempe 等ICCV 2025 · 被引用 15 次
它引用的顶会 Paper27
- Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the LoopNikos Kolotouros, Georgios Pavlakos, Michael J. Black, Kostas DaniilidisICCV 2019 · 被引用 1,139 次
- Tracking Without Bells and WhistlesPhilipp Bergmann, Tim Meinhardt, Laura Leal-TaixéICCV 2019 · 被引用 1,030 次
- TrackFormer: Multi-Object Tracking with TransformersTim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph FeichtenhoferCVPR 2022 · 被引用 927 次
- PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback LoopHongwen Zhang, Yating Tian, Xinchi Zhou, Wanli Ouyang 等ICCV 2021 · 被引用 376 次
- Deep Patch Visual OdometryZachary Teed, Lahav Lipson, Jia DengNeurIPS 2023 · 被引用 323 次
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