CRISP: Progressive Illumination Curriculum for Recurrent Low-Light Video Enhancement with Semantic Priors
Low-light video enhancement requires the recovery of brightness, color, and fine spatial structures while preserving temporal coherence in the presence of noise and motion. Existing methods often struggle to balance these objectives, particularly in severely degraded regions. This paper presents CRISP, a recurrent framework trained using a progressive illumination curriculum. Its two-frame recurrent architecture propagates information across successive frames to exploit temporal context beyond the immediate input pair. During training, supervision progressively transitions from intermediate targets interpolated between the low-light input and the reference to the full reference, gradually...
| Authors | Ruirui Lin, Xin Yan Lim, Yini Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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