mlsanityData to 7 Oct 2026

SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation

arXiv 1902.10099 ↗First posted 26 Feb 2019cs.CVcited by 6

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Abstract (arXiv)

State-of-the-art scene flow algorithms pursue the conflicting targets of accuracy, run time, and robustness. With the successful concept of pixel-wise matching and sparse-to-dense interpolation, we push the limits of scene flow estimation. Avoiding strong assumptions on the domain or the problem yields a more robust algorithm. This algorithm is fast because we avoid explicit regularization during matching, which allows an efficient computation. Using image information from multiple time steps and explicit visibility prediction based on previous results, we achieve competitive performances on different data sets. Our contributions and results are evaluated in comparative experiments. Overall, we present an accurate scene flow algorithm that is faster and more generic than any individual benchmark leader.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Feb 2019.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 3; 2025: 0; 2026: 1.

6 papers.