Research map / 3D vision / Face and shape
BodyMap: Learning Full-Body Dense Correspondence Map
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add CSE correspondence input alongside RGB (ablation) | BodyMap · DensePose-COCO | 2D correspondence accuracy, 5 px: 61.18 -> 65.34 | Helped |
| replace the ViT backbone with U-Net (ablation) | BodyMap · Synthetic Dataset | 2D correspondence accuracy, 5 px: 68.42 -> 71.12 | Hurt |
| replace the ViT backbone with U-Net (ablation) | BodyMap · DensePose-COCO | 2D correspondence accuracy, 5 px: 60.82 -> 65.34 | Hurt |
| add silhouette loss (ablation) | BodyMap with classification loss · Synthetic Dataset | 2D correspondence accuracy, 5 px: 65.16 -> 69.18 | Helped |
| add geodesic loss (ablation) | BodyMap with classification and silhouette losses · DensePose-COCO | 2D correspondence accuracy, 5 px: 54.12 -> 61.83 | Helped |
| add consistency loss (ablation) | BodyMap with classification, silhouette, and geodesic losses · DensePose-COCO | 2D correspondence accuracy, 5 px: 61.83 -> 65.34 | Helped |
| add geodesic loss (ablation) | BodyMap with classification and silhouette losses · Synthetic Dataset | 2D correspondence accuracy, 5 px: 69.18 -> 70.23 | Helped |
| fine-tune on DensePose-COCO using sparse annotations (ablation) | BodyMap · DensePose-COCO | 2D correspondence accuracy, 5 px: 40.51 -> 56.12 | Helped |
| use dense pseudo-ground-truth fine-tuning instead of sparse-annotation fine-tuning (ablation) | BodyMap · DensePose-COCO | 2D correspondence accuracy, 5 px: 56.12 -> 65.34 | Helped |
| use dense pseudo-ground-truth fine-tuning instead of sparse-annotation fine-tuning (ablation) | BodyMap · DensePose-COCO | 3D AP: 70.3 -> 79.5 | Helped |
Closest papers by meaning
- Dense Human Body Correspondences Using Convolutional Networks (CVPR 2016 · similarity 0.92)
- DensePose: Dense Human Pose Estimation in the Wild (CVPR 2018 · similarity 0.90)
- SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements (CVPR 2021 · similarity 0.89)
- Learning 3D Texture-Aware Representations for Parsing Diverse Human Clothing and Body Parts (AAAI 2026 · similarity 0.88)
- SCULPT: Shape-Conditioned Unpaired Learning of Pose-dependent Clothed and Textured Human Meshes (CVPR 2024 · similarity 0.87)
- MultiGO: Towards Multi-level Geometry Learning for Monocular 3D Textured Human Reconstruction (CVPR 2025 · similarity 0.86)
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