Research map / 3D vision / Depth and stereo
High-Quality Depth From Uncalibrated Small Motion Clip
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use intensity-profile variance instead of pairwise SAD for plane-sweeping matching (ablation) | Dense stereo matching · Synthetic clip (b = −2.1, n = 31) | MAD: 8.650 -> 5.763 | Helped |
| Use intensity-profile variance instead of pairwise SAD for plane-sweeping matching (ablation) | Dense stereo matching · Synthetic clip (b = −2.1, n = 31) | R5: 64.940 -> 67.728 | Helped |
| Use intensity-profile variance instead of pairwise SAD for plane-sweeping matching (ablation) | Dense stereo matching · Synthetic clip (b = −2.1, n = 31) | R10: 86.419 -> 90.201 | Helped |
| Estimate focal length and radial distortion jointly with camera poses and scene points | Small-motion bundle adjustment · Small-motion camera clips | distortion error (pixel): 5.76 -> 0.52; 5.89 -> 0.53; 3.65 -> 1.48; 3.25 -> 1.14 | Helped |
| Use more than 30 frames and a baseline greater than 1% of the nearest scene depth | Proposed depth reconstruction · Synthetic small-motion clips | R5: around 80% | Helped |
Closest papers by meaning
- Depth Pro: Sharp Monocular Metric Depth in Less Than a Second (ICLR 2025 · similarity 0.85)
- Depth2Pose: A Pose-Based Benchmark for Monocular Depth Estimation without Ground-Truth Depth (NeurIPS 2026 · similarity 0.84)
- Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving (CVPR 2024 · similarity 0.84)
- DiffCalib: Reformulating Monocular Camera Calibration as Diffusion-Based Dense Incident Map Generation (AAAI 2025 · similarity 0.84)
- A Simple yet Universal Framework for Depth Completion (NeurIPS 2024 · similarity 0.83)
- Seurat: From Moving Points to Depth (CVPR 2025 · similarity 0.83)
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