In this study, we focus on the problem of 3D human mesh recovery from a single image under obscured conditions. Most state-of-the-art methods aim to improve 2D alignment technologies, such as spatial averaging and 2D joint sampling. However, they tend to neglect the crucial aspect of 3D alignment by improving 3D representations. Furthermore, recent methods struggle to separate the target human from occlusion or background in crowded scenes as they optimize the 3D space of target human with 3D joint coordinates as local supervision. To address these issues, a desirable method would involve a framework for fusing 2D and 3D features and a strategy for optimizing the 3D space globally. Therefore, this paper presents 3D JOint contrastive learning with TRansformers (JOTR) framework for handling occluded 3D human mesh recovery. Our method includes an encoder-decoder transformer architecture to fuse 2D and 3D representations for achieving 2D$\&$3D aligned results in a coarse-to-fine manner and a novel 3D joint contrastive learning approach for adding explicitly global supervision for the 3D feature space. The contrastive learning approach includes two contrastive losses: joint-to-joint contrast for enhancing the similarity of semantically similar voxels (i.e., human joints), and joint-to-non-joint contrast for ensuring discrimination from others (e.g., occlusions and background). Qualitative and quantitative analyses demonstrate that our method outperforms state-of-the-art competitors on both occlusion-specific and standard benchmarks, significantly improving the reconstruction of occluded humans.

翻译：本研究聚焦于单张图像在遮挡条件下的三维人体网格恢复问题。当前主流方法致力于改进二维对齐技术（如空间平均与二维关节采样），却忽视了通过优化三维表示实现三维对齐的关键环节。此外，近年方法在拥挤场景中难以将目标人体与遮挡物或背景分离，因其仅以三维关节坐标为局部监督信号优化目标人体三维空间。为此，理想方案需构建融合二维与三维特征的框架，并采用全局优化三维空间的策略。本文提出基于Transformer的三维关节对比学习（JOTR）框架，用于处理遮挡下的三维人体网格恢复。该方法采用编码器-解码器Transformer架构，以由粗到精的方式融合二维与三维表示，实现二维与三维对齐结果；同时引入新型三维关节对比学习方法，为三维特征空间施加显式全局监督。该对比学习包含两种对比损失：关节间对比增强语义相似体素（如人体关节）的相似性，关节-非关节对比确保与其它元素（如遮挡物与背景）的区分性。定性与定量分析表明，本方法在遮挡专用基准与标准基准上均超越现有最优技术，显著提升了遮挡人体的重建质量。