most citedSingle-Image Shadow Removal Using Deep Learning: A Comprehensive Survey

3 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Self-DACE++: Robust Low-Light Enhancement via Efficient Adaptive Curve Estimation

Jianyu Wen, Jun Xie, Feng Chen +5

In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our previous Self-Reference Deep Ada…

cs.CV2026

Spectral Defense Against Resource-Targeting Attack in 3D Gaussian Splatting

Yang Chen, Yi Yu, Jiaming He +3

Recent advances in 3D Gaussian Splatting (3DGS) deliver high-quality rendering, yet the Gaussian representation exposes a new attack surface, the resource-targeting attack. This at…

cs.CV2024

Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior

Yi Yu, Yufei Wang, Wenhan Yang +5

Recent advancements in deep learning-based compression techniques have surpassed traditional methods. However, deep neural networks remain vulnerable to backdoor attacks, where pre…

cs.CV2024★ 3 cited

Single-Image Shadow Removal Using Deep Learning: A Comprehensive Survey

Laniqng Guo, Chong Wang, Yufei Wang +5

Shadow removal aims at restoring the image content within shadow regions, pursuing a uniform distribution of illumination that is consistent between shadow and non-shadow regions.…

cs.CV2024

Benchmarking Adversarial Robustness of Image Shadow Removal with Shadow-adaptive Attacks

Chong Wang, Yi Yu, Lanqing Guo +1

Shadow removal is a task aimed at erasing regional shadows present in images and reinstating visually pleasing natural scenes with consistent illumination. While recent deep learni…

eess.IV2024

Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI

Chong Wang, Lanqing Guo, Yufei Wang +3

Deep unfolding networks (DUN) have emerged as a popular iterative framework for accelerated magnetic resonance imaging (MRI) reconstruction. However, conventional DUN aims to recon…