AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference
Researchers have developed AMNet, a novel multimodal framework for low-light video enhancement (LLVE) that can perform inference even when auxiliary data like infrared or event streams are unavailable. The system uses a Spatial-Spectral Dual-Gated Translator to generate implicit representations from RGB inputs, enabling robust enhancement. Extensive experiments show AMNet's superior performance in modality-absent conditions, with code and models publicly released. AI
IMPACT This framework could improve video analysis and capture in challenging lighting conditions, potentially impacting surveillance, autonomous driving, and photography.