第8届HANDS Workshop挑战赛ARCTIC赛道第一名解决方案：基于3DGS的双手类别无关交互重建
1st Place Solution to the 8th HANDS Workshop Challenge -- ARCTIC Track: 3DGS-based Bimanual Category-agnostic Interaction Reconstruction
AI总结：
针对ECCV 2024第8届HANDS挑战赛ARCTIC赛道的双手类别无关手物交互重建任务，提出结合掩码损失、3D接触损失的3DGS方案，在测试集主指标CD$_h$达38.69获第一名。
摘要：
本报告介绍了我们在ECCV 2024同期举办的第8届HANDS Workshop挑战赛ARCTIC赛道中获得第一名的解决方案。本次挑战赛的任务是双手类别无关的手-物交互重建，目标是在不依赖预定义模板的情况下，从单目视频生成双手与物体的3D重建结果。由于双手操作过程中手与物体之间存在严重遮挡和动态接触，该任务极具挑战性。我们分别引入掩码损失和3D接触损失来解决这些问题，此外还将3D Gaussian Splatting（3DGS，三维高斯泼溅）应用于该任务。最终，我们的方法在ARCTIC测试集上的主要指标CD$_h$取得了38.69的成绩。
英文摘要：
This report describes our 1st place solution to the 8th HANDS workshop challenge (ARCTIC track) in conjunction with ECCV 2024. In this challenge, we address the task of bimanual category-agnostic hand-object interaction reconstruction, which aims to generate 3D reconstructions of both hands and the object from a monocular video, without relying on predefined templates. This task is particularly challenging due to the significant occlusion and dynamic contact between the hands and the object during bimanual manipulation. We worked to resolve these issues by introducing a mask loss and a 3D contact loss, respectively. Moreover, we applied 3D Gaussian Splatting (3DGS) to this task. As a result, our method achieved a value of 38.69 in the main metric, CD$_h$, on the ARCTIC test set.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
