Research map / 3D vision / Depth and stereo
Polka Lines: Learning Structured Illumination and Reconstruction for Active Stereo
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Optimize the illumination pattern jointly with the reconstruction network instead of using a hand-crafted pattern | Active stereo · Synthetic indoor environments | depth reconstruction accuracy | Helped |
| Use the learned Polka Lines pattern instead of the Intel RealSense D415 pattern | Active stereo · High dynamic range scenes | depth reconstruction robustness | Helped |
| Add illumination-image features and narrow-baseline cues to the binocular camera inputs (ablation) | Trinocular active stereo network · Occluded regions | depth estimation stability | Helped |
| Add a Polka Lines illumination pattern to passive stereo | Active stereo · High dynamic range scene conditions | depth estimation accuracy | Helped |
| Use a generic-environment pattern rather than an indoor-specific pattern | Polka Lines active stereo · Low-reflectance objects | depth estimation accuracy | Helped |
Closest papers by meaning
- Optimal Structured Light à La Carte (CVPR 2018 · similarity 0.89)
- UltraStereo: Efficient Learning-Based Matching for Active Stereo Systems (CVPR 2017 · similarity 0.89)
- Connecting the Dots: Learning Representations for Active Monocular Depth Estimation (CVPR 2019 · similarity 0.89)
- TurboSL: Dense Accurate and Fast 3D by Neural Inverse Structured Light (CVPR 2024 · similarity 0.87)
- Active Event-based Stereo Vision (CVPR 2025 · similarity 0.87)
- Learned Binocular-Encoding Optics for RGBD Imaging Using Joint Stereo and Focus Cues (CVPR 2025 · similarity 0.84)
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