6 papers
EvoIR-Agent: Self-Evolving Image Restoration Agentic System via Experience-Driven Learning
Kailin Zhuang, Jiawei Wu, Zhi Jin
Multimodal Large Language Model (MLLM)-driven image restoration agent demonstrates effectiveness in degradation coupling scenarios by flexibly selecting tools and determining remov…
Unifying Heterogeneous Degradations: Uncertainty-Aware Diffusion Bridge Model for All-in-One Image Restoration
Luwei Tu, Jiawei Wu, Xing Luo +1
All-in-One Image Restoration (AiOIR) faces the fundamental challenge in reconciling conflicting optimization objectives across heterogeneous degradations. Existing methods are ofte…
Gradient as Conditions: Rethinking HOG for All-in-one Image Restoration
Jiawei Wu, Zhifei Yang, Zhe Wang +1
All-in-one image restoration (AIR) aims to address diverse degradations within a unified model by leveraging informative degradation conditions to guide the restoration process. Ho…
MotionDiff: Training-free Zero-shot Interactive Motion Editing via Flow-assisted Multi-view Diffusion
Yikun Ma, Yiqing Li, Jiawei Wu +2
Generative models have made remarkable advancements and are capable of producing high-quality content. However, performing controllable editing with generative models remains chall…
SparseGS-W: Sparse-View 3D Gaussian Splatting in the Wild with Generative Priors
Yiqing Li, Xuan Wang, Jiawei Wu +2
Synthesizing novel views of large-scale scenes from unconstrained in-the-wild images is an important but challenging task in computer vision. Existing methods, which optimize per-i…
Unsupervised Variational Translator for Bridging Image Restoration and High-Level Vision Tasks
Jiawei Wu, Zhi Jin
Recent research tries to extend image restoration capabilities from human perception to machine perception, thereby enhancing the performance of high-level vision tasks in degraded…