Chenxu Zhou, Zhiyuan Yu, Yudong Jin, Yinji Shentu, Yu Zhang, Jiaming Sun, Xiaowei Zhou · 2026 · arXiv
DOI: 10.48550/arXiv.2610.30023 · open-access PDF
本文解决了从稀缺和低分辨率的捕捉资源创建沉浸式体积视频的问题。传统的密集多视图重建方法可以产生高质量的体积视频,但它们依赖昂贵的捕捉设置使得它们在现实世界的场景中不实用。最近的方法使用生成模型来放松捕捉需求,但仍然受到有限的分辨率和4D不一致的影响。
Machine translation (Meta M2M100); the English original follows.
This paper addresses the problem of creating immersive volumetric videos from sparse and low-resolution capture resources. Conventional dense multi-view reconstruction methods can produce high-quality volumetric videos, but their reliance on costly capture setups makes them impractical in real-world scenarios. Recent approaches use generative models to relax capture requirements, but still suffer from limited resolution and 4D inconsistency. To overcome these constraints, we propose RealMe, a unified framework built around a high-resolution video diffusion model that enhances limited captures
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