EIC-LIE uses an event-illumination collaborative module and illumination-aware event filter plus a new real-world dataset to improve low-light image enhancement over prior methods.
Fouriermamba: Fourier learning integration with state space models for image deraining
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
other 1
citation-polarity summary
fields
cs.CV 4years
2026 4representative citing papers
EventGait is a dual-stream spiking and cross-modal framework for event-based gait recognition that matches or exceeds RGB methods in normal conditions and significantly outperforms them in low light, supported by new synthetic event gait benchmarks.
GS-STVSR achieves state-of-the-art continuous spatio-temporal video super-resolution quality with nearly constant inference time at standard scales and over 3x speedup at extreme scales using 2D Gaussian Splatting.
TPGDiff introduces hierarchical triple-prior guidance in a diffusion network, placing degradation priors throughout, structural priors in shallow layers, and semantic priors in deep layers for improved all-in-one image restoration.
citing papers explorer
-
Event-Illumination Collaborative Low-light Image Enhancement with a High-resolution Real-world Dataset
EIC-LIE uses an event-illumination collaborative module and illumination-aware event filter plus a new real-world dataset to improve low-light image enhancement over prior methods.
-
EventGait: Towards Robust Gait Recognition with Event Streams
EventGait is a dual-stream spiking and cross-modal framework for event-based gait recognition that matches or exceeds RGB methods in normal conditions and significantly outperforms them in low light, supported by new synthetic event gait benchmarks.
-
GS-STVSR: Ultra-Efficient Continuous Spatio-Temporal Video Super-Resolution via 2D Gaussian Splatting
GS-STVSR achieves state-of-the-art continuous spatio-temporal video super-resolution quality with nearly constant inference time at standard scales and over 3x speedup at extreme scales using 2D Gaussian Splatting.
-
TPGDiff: Hierarchical Triple-Prior Guided Diffusion for Image Restoration
TPGDiff introduces hierarchical triple-prior guidance in a diffusion network, placing degradation priors throughout, structural priors in shallow layers, and semantic priors in deep layers for improved all-in-one image restoration.