arXiv Computer Vision
ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark
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arXiv Computer Vision
Oct 15
OLiVES: An Outdoor Low-Light Video Benchmark for Enhancement and Segmentation
arXiv:2610.20501v1 Announce Type: new Abstract: Low-light video processing remains an underexplored problem in computer vision, primarily due to the scarcity of high-quality ground-truth data. Existi...
arXiv Computer Vision
Oct 8
LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting
arXiv:2607.08016v3 Announce Type: replace Abstract: Video relighting requires balancing long-form temporal consistency with a physically grounded understanding of light transport, which depends on ac...
arXiv Computer Vision
Sep 23
MirrorDistill: Illumination-Aware Latent Distillation for Efficient Low-Light Restoration
MirrorDistill introduces an illumination‑aware latent distillation framework for low‑light image enhancement. It trains a lightweight student encoder‑decoder by aligning its intermediate features with clean‑domain targets generated by a teacher decoder, using feature mirroring and illumination‑aware weighting to emphasize underexposed regions. The method achieves state‑of‑the‑art performance on the LOL‑v2‑Real benchmark while maintaining the lowest computational complexity, and the code is released as open source.
Hugging Face Trending Papers
Jun 28
EvLIR: Learning Illumination Residuals from Ordered Events for Low-Light Image Enhancement
Low-light image enhancement is severely ill-posed when the input frame contains missing structure, saturated noise, and weak local contrast. Event cameras provide asynchronous brightness-change observations with high temporal resolution, but prior works often treat voxel channels as an unordered or static feature stack before fusion, rather than explicitly modeling their within-window temporal evolution, weakening the temporal evidence that makes events useful.
arXiv Computer Vision
1d ago
EditDistill: Is It Possible to Guide Video Editing with Image Editing?
arXiv:2610.34303v1 Announce Type: new Abstract: Recent advances in image editing have enabled fine-grained and highly controllable visual modifications. However, achieving similar levels of controlla...
arXiv Computer Vision
Sep 1
DARD: Zero-Shot Degradation-Aware Retinex-Guided Diffusion for Low-Light Image Enhancement
arXiv:2608.29243v1 Announce Type: new Abstract: Existing diffusion-based enhancement methods provide strong generative capability for low-light image enhancement (LLIE), yet they either rely on paire...