VALSE 论文速览 第141期：基于注意力聚合与表征解耦的任意交互双手重建 ...

论文题目：Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction

作者列表：

余正谛 (杜伦大学)，黄少立 (腾讯 AI Lab)，Chen Fang (腾讯AI Lab)，Toby Breckon (杜伦大学)，王珏 (腾讯AI Lab)

B站观看网址：

https://www.bilibili.com/video/BV1B84y197SD/

论文摘要：

Reconstructing two hands from monocular RGB images is challenging due to frequent occlusion and mutual confusion. Existing methods mainly learn an entangled representation to encode two interacting hands, which are incredibly fragile to impaired interaction, such as truncated hands, separate hands, or external occlusion. This paper presents ACR (Attention Collaboration based Regressor), which makes the first attempt to reconstruct hands in arbitrary scenarios. To achieve this, ACR explicitly mitigates interdependencies between hands and between parts by leveraging center and part-based attention for feature extraction. However, reducing interdependence helps release the input constraint while weakening the mutual reasoning about reconstructing the interacting hands. Thus, based on center attention, ACR also learns cross-hand prior that handle the interacting hands better. We evaluate our method on various types of hand reconstruction datasets. Our method significantly outperforms the best interacting-hand approaches on the InterHand2.6M dataset while yielding comparable performance with the state-of-the-art single-hand methods on the FreiHand dataset. More qualitative results on in-the-wild and hand-object interaction datasets and web images/videos further demonstrate the effectiveness of our approach for arbitrary hand reconstruction. 

论文信息：

[1] Zhengdi Yu, Shaoli Huang, Chen Fang, Toby P. Breckon, Jue Wang, Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction, In CVPR, 2023.

论文链接：

[https://arxiv.org/abs/2303.05938]

代码链接：

[https://github.com/ZhengdiYu/Arbitrary-Hands-3D-Reconstruction]

视频讲者简介：

余正谛，帝国理工博士在读，此文为作者在Tencent AI Lab视觉计算中心实习完成的工作。

特别鸣谢本次论文速览主要组织者：

月度轮值AC：焦剑波 (伯明翰大学)

季度轮值AC：叶茫 (武汉大学)