Back to the Future Cyclopean Stereo: a human perception approach combining deep and geometric constraints
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Abstract (arXiv)
We innovate in stereo vision by explicitly providing analytical 3D surface models as viewed by a cyclopean eye model that incorporate depth discontinuities and occlusions. This geometrical foundation combined with learned stereo features allows our system to benefit from the strengths of both approaches. We also invoke a prior monocular model of surfaces to fill in occlusion regions or texture-less regions where data matching is not sufficient. Our results already are on par with the state-of-the-art purely data-driven methods and are of much better visual quality, emphasizing the importance of the 3D geometrical model to capture critical visual information. Such qualitative improvements may find applicability in virtual reality, for a better human experience, as well as in robotics, for reducing critical errors. Our approach aims to demonstrate that understanding and modeling geometrical properties of 3D surfaces is beneficial to computer vision research.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 28 references that are in the map. First posted on arXiv 28 Feb 2025.
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References · 14
- 2021Vision Transformers for Dense Predictioncited by 1,803
- 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,495
- 2024Depth Anything V2cited by 1,422
- 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,360
- 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 657
- 2022Activating More Pixels in Image Super-Resolution Transformercited by 438
- 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 404
- 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 395
- 2024UniDepth: Universal Monocular Metric Depth Estimationcited by 382
- 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 365
- 2021RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matchingcited by 353
- 2022Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlationcited by 197
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