Guess The Unseen: Dynamic 3D Scene Reconstruction from Partial 2D Glimpses
Inhee Lee, Byungjun Kim, Hanbyul Joo
2024年份
9顶会引用
摘要
Input: Monocular Video Novel Pose Synthesis Novel View Synthesis Output: Animatable Person 3D-GS Occluded partial observations For Teaser (light) Figure 1. We present a method to reconstruct dynamic scenes from a monocular video capturing partial 2D observations. As a key advantage, our method can estimate the unseen body parts by leveraging a pre-trained diffusion model [40] via SDS method [37]. The reconstructed scenes can be rendered to any viewpoint and each human body can be transformed into any body posture controlled by SMPL [27] parameters.
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引用它的顶会 Paper9
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它引用的顶会 Paper39
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 被引用 35,902 次
- Segment AnythingAlexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao 等ICCV 2023 · 被引用 13,211 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li 等NeurIPS 2022 · 被引用 8,965 次
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