Research map / 3D vision / Depth and stereo
Beyond Row Alignment: Virtual-Camera-Aware Online Stereo Rectification
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AI-extracted summary. Written by AI from the paper's abstract only. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Proposes virtual-camera-aware online stereo rectification to correct small post-calibration shifts in stereo camera pairs so stereo matchers keep accurate depth.
Problem
Stereo matchers assume accurately calibrated and rectified cameras, but small physical shifts after calibration (camera motion, mechanical drift, vibration, installation changes) break this assumption and degrade depth estimation.
Approach
Online rectification that is aware of a virtual camera, going beyond simple row alignment; the abstract is truncated so the specific mechanism is not stated.
Closest papers by meaning
- Rectification-specific Supervision and Constrained Estimator for Online Stereo Rectification (CVPR 2025 · similarity 0.94)
- Flow-Guided Online Stereo Rectification for Wide Baseline Stereo (CVPR 2024 · similarity 0.92)
- MonSter: Marry Monodepth to Stereo Unleashes Power (CVPR 2025 · similarity 0.87)
- DEFOM-Stereo: Depth Foundation Model Based Stereo Matching (CVPR 2025 · similarity 0.87)
- Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail (CVPR 2025 · similarity 0.87)
- Any-Stereo: Arbitrary Scale Disparity Estimation for Iterative Stereo Matching (AAAI 2024 · similarity 0.87)
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