Research map / 3D vision / Face and shape
FroDO: From Detections to 3D Objects
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the inferred 3D bounding-box occlusion filter (ablation) | FroDO · Redwood-OS Vote | CD [cm]: 12.17 -> 11.97 | Helped |
| Use the inferred 3D bounding-box occlusion filter (ablation) | FroDO · Redwood-OS Average | CD [cm]: 11.73 -> 10.57 | Helped |
| Use sparse rather than dense optimization | FroDO · 60-frame sequence | sec. /iteration: 4.96 -> 0.07 | Helped |
| Use sparse optimization rather than PMO | FroDO · 60-frame sequence | sec. /iteration: 12.59 -> 0.07 | Helped |
Closest papers by meaning
- From Points to Multi-Object 3D Reconstruction (CVPR 2021 · similarity 0.88)
- Amodal Detection of 3D Objects: Inferring 3D Bounding Boxes From 2D Ones in RGB-Depth Images (CVPR 2017 · similarity 0.86)
- Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild (CVPR 2023 · similarity 0.85)
- Free-Moving Object Reconstruction and Pose Estimation with Virtual Camera (AAAI 2025 · similarity 0.85)
- Duoduo CLIP: Efficient 3D Understanding with Multi-View Images (ICLR 2025 · similarity 0.84)
- In-Hand 3D Object Reconstruction from a Monocular RGB Video (AAAI 2024 · similarity 0.84)
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