mlsanityData to 14 Oct 2026

Low-Light Video Enhancement via Spatial-Temporal Consistent Decomposition

arXiv 2405.15660 ↗First posted 24 May 2024cs.CVcited by 6

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Abstract (arXiv)

Low-Light Video Enhancement (LLVE) seeks to restore dynamic or static scenes plagued by severe invisibility and noise. In this paper, we present an innovative video decomposition strategy that incorporates view-independent and view-dependent components to enhance the performance of LLVE. We leverage dynamic cross-frame correspondences for the view-independent term (which primarily captures intrinsic appearance) and impose a scene-level continuity constraint on the view-dependent term (which mainly describes the shading condition) to achieve consistent and satisfactory decomposition results. To further ensure consistent decomposition, we introduce a dual-structure enhancement network featuring a cross-frame interaction mechanism. By supervising different frames simultaneously, this network encourages them to exhibit matching decomposition features. This mechanism can seamlessly integrate with encoder-decoder single-frame networks, incurring minimal additional parameter costs. Extensive experiments are conducted on widely recognized LLVE benchmarks, covering diverse scenarios. Our framework consistently outperforms existing methods, establishing a new SOTA performance.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 20 of its 39 references that are in the map. First posted on arXiv 24 May 2024.

Builds on

20 of 39 references.

References · 20

  1. 2017Attention Is All You Needcited by 60,361
  2. 2017The 2017 DAVIS Challenge on Video Object Segmentationcited by 957
  3. 2019EnlightenGAN: Deep Light Enhancement without Paired Supervisioncited by 466
  4. 2023RoMa: Robust Dense Feature Matchingcited by 302
  5. 2018Learning Blind Video Temporal Consistencycited by 253
  6. 2023Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancementcited by 231
  7. 2023Tracking Everything Everywhere All at Oncecited by 193
  8. 2022DKM: Dense Kernelized Feature Matching for Geometry Estimationcited by 177
  9. 2017DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networkscited by 156
  10. 2023Low-Light Image Enhancement via Structure Modeling and Guidancecited by 79
  11. 2022A Simple Baseline for Video Restoration with Grouped Spatial-temporal Shiftcited by 68
  12. 2024Zero-Reference Low-Light Enhancement via Physical Quadruple Priorscited by 58
8 more
  1. 2023Lighting up NeRF via Unsupervised Decomposition and Enhancementcited by 40
  2. 2015Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regressioncited by 33
  3. 2022Low-Light Video Enhancement with Synthetic Event Guidancecited by 33
  4. 2023PMatch: Paired Masked Image Modeling for Dense Geometric Matchingcited by 29
  5. 2020Low Light Video Enhancement using Synthetic Data Produced with an Intermediate Domain Mappingcited by 26
  6. 2024Binarized Low-light Raw Video Enhancementcited by 17
  7. 2022Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super Resolutioncited by 10
  8. 2022Low Light Video Enhancement by Learning on Static Videos with Cross-Frame Attentioncited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 5.

6 papers.