most citedContinual Test-Time Adaptation for Single Image Defocus Deblurring via Causal Siamese Networks

4 citations · 4 across the 4 of their papers we have counts for

collaborators

6 papers

cs.IR2026

D3ER: Supporting Multi-Modal Recommendation via Disentangle and Distillation-based Dynamic Ensemble

Bingnan Wang, Yi Li, Xiongxin Tang +2

Incorporating items' information shared among multiple modalities into a fused representation, multi-modal recommendation (MR) has demonstrated documented success than canonical un…

cs.CV2026

LoViF 2026 The First Challenge on Unified Removal of Raindrops and Reflections: Methods and Results

Zewei He, Xi Tong, Yu Chen +49

This workshop paper comprehensively reviews the First Challenge on Unified Removal of Raindrops and Reflections. The challenge aims to address a frequently encountered practical pr…

cs.CV2026

Self-Evolving Agentic Image Restoration via Deliberate Planning and Intuitive Execution

Shuang Cui, Fan Ji, Guanglong Sun +4

Real-world image restoration (IR) remains challenging due to complex and coupled degradations. While recent agentic IR frameworks leverage Large Language Models for flexible tool p…

cs.CV2025

BayesTTA: Continual-Temporal Test-Time Adaptation for Vision-Language Models via Gaussian Discriminant Analysis

Shuang Cui, Jinglin Xu, Yi Li +6

Vision-language models (VLMs) such as CLIP achieve strong zero-shot recognition but degrade significantly under \textit{temporally evolving distribution shifts} common in real-worl…

cs.CV2025

3D-UIR: 3D Gaussian for Underwater 3D Scene Reconstruction via Physics Based Appearance-Medium Decoupling

Jieyu Yuan, Yujun Li, Yuanlin Zhang +4

Novel view synthesis for underwater scene reconstruction presents unique challenges due to complex light-media interactions. Optical scattering and absorption in water body bring i…

eess.IV20254 cited

Continual Test-Time Adaptation for Single Image Defocus Deblurring via Causal Siamese Networks

Shuang Cui, Yi Li, Jiangmeng Li +4

Single image defocus deblurring (SIDD) aims to restore an all-in-focus image from a defocused one. Distribution shifts in defocused images generally lead to performance degradation…