5 papers
REVEAL: Reference-Grounded Reasoning for Multimodal Manipulation Detection
Jun Zhou, Bingwen Hu, Yaxiong Wang +4
Multimodal manipulation detection aims to simultaneously identify forged image--text pairs and localize tampered regions, yet existing methods typically rely on memorizing isolated…
M2IR: Proactive All-in-One Image Restoration via Mamba-style Modulation and Mixture-of-Experts
Shiwei Wang, Yongzhen Wang, Bingwen Hu +3
While Transformer-based architectures have dominated recent advances in all-in-one image restoration, they remain fundamentally reactive: propagating degradations rather than proac…
Laplace-Mamba: Laplace Frequency Prior-Guided Mamba-CNN Fusion Network for Image Dehazing
Yongzhen Wang, Liangliang Chen, Bingwen Hu +3
Recent progress in image restoration has underscored Spatial State Models (SSMs) as powerful tools for modeling long-range dependencies, owing to their appealing linear complexity…
Unwarping Screen Content Images via Structure-texture Enhancement Network and Transformation Self-estimation
Zhenzhen Xiao, Heng Liu, Bingwen Hu
While existing implicit neural network-based image unwarping methods perform well on natural images, they struggle to handle screen content images (SCIs), which often contain large…
CLIP-SR: Collaborative Linguistic and Image Processing for Super-Resolution
Bingwen Hu, Heng Liu, Zhedong Zheng +1
Convolutional Neural Networks (CNNs) have significantly advanced Image Super-Resolution (SR), yet most CNN-based methods rely solely on pixel-based transformations, often leading t…