WinT3R: Window-Based Streaming Reconstruction with Camera Token Pool

• URL: http://arxiv.org/abs/2509.05296v1
• Date: Fri, 05 Sep 2025 17:59:47 GMT
• Title: WinT3R: Window-Based Streaming Reconstruction with Camera Token Pool
• Authors: Zizun Li, Jianjun Zhou, Yifan Wang, Haoyu Guo, Wenzheng Chang, Yang Zhou, Haoyi Zhu, Junyi Chen, Chunhua Shen, Tong He,
• Abstract summary: WinT3R is a feed-forward reconstruction model capable of online prediction of precise camera poses and high-quality point maps.<n>We introduce a sliding window mechanism that ensures sufficient information exchange among frames within the window.<n>We leverage a compact representation of cameras and maintain a global camera token pool, which enhances the reliability of camera pose estimation.
• Score: 54.93856767365114
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present WinT3R, a feed-forward reconstruction model capable of online prediction of precise camera poses and high-quality point maps. Previous methods suffer from a trade-off between reconstruction quality and real-time performance. To address this, we first introduce a sliding window mechanism that ensures sufficient information exchange among frames within the window, thereby improving the quality of geometric predictions without large computation. In addition, we leverage a compact representation of cameras and maintain a global camera token pool, which enhances the reliability of camera pose estimation without sacrificing efficiency. These designs enable WinT3R to achieve state-of-the-art performance in terms of online reconstruction quality, camera pose estimation, and reconstruction speed, as validated by extensive experiments on diverse datasets. Code and model are publicly available at https://github.com/LiZizun/WinT3R.

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