5 papers · 1 filter
Low-Light Image Enhancement via Generative Perceptual Priors
Han Zhou, Wei Dong, Xiaohong Liu +3
Although significant progress has been made in enhancing visibility, retrieving texture details, and mitigating noise in Low-Light (LL) images, the challenge persists in applying c…
ECMamba: Consolidating Selective State Space Model with Retinex Guidance for Efficient Multiple Exposure Correction
Wei Dong, Han Zhou, Yulun Zhang +2
Exposure Correction (EC) aims to recover proper exposure conditions for images captured under over-exposure or under-exposure scenarios. While existing deep learning models have sh…
GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrieval
Han Zhou, Wei Dong, Xiaohong Liu +4
Most existing Low-light Image Enhancement (LLIE) methods either directly map Low-Light (LL) to Normal-Light (NL) images or use semantic or illumination maps as guides. However, the…
ShadowRefiner: Towards Mask-free Shadow Removal via Fast Fourier Transformer
Wei Dong, Han Zhou, Yuqiong Tian +4
Shadow-affected images often exhibit pronounced spatial discrepancies in color and illumination, consequently degrading various vision applications including object detection and s…
DehazeDCT: Towards Effective Non-Homogeneous Dehazing via Deformable Convolutional Transformer
Wei Dong, Han Zhou, Ruiyi Wang +3
Image dehazing, a pivotal task in low-level vision, aims to restore the visibility and detail from hazy images. Many deep learning methods with powerful representation learning cap…