mlsanityData to 7 Oct 2026

CrevNet: Conditionally Reversible Video Prediction

arXiv 1910.11577 ↗First posted 25 Oct 2019cs.CV cs.LGcited by 15

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Abstract (arXiv)

Applying resolution-preserving blocks is a common practice to maximize information preservation in video prediction, yet their high memory consumption greatly limits their application scenarios. We propose CrevNet, a Conditionally Reversible Network that uses reversible architectures to build a bijective two-way autoencoder and its complementary recurrent predictor. Our model enjoys the theoretically guaranteed property of no information loss during the feature extraction, much lower memory consumption and computational efficiency.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Oct 2019.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 5; 2024: 2; 2025: 2; 2026: 1.

15 papers.

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