Low-Light Video Enhancement via Spatial-Temporal Consistent Decomposition
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Low-light Video Enhancement | DID (test) | PSNR30.1 | 13 | |
| Low-light Video Enhancement | SDSD indoor (test) | PSNR28.93 | 8 | |
| Low-light Video Enhancement | SDSD Outdoor (test) | PSNR26.32 | 8 |