7 papers
SkillIR: Evolving Scene-Aware Skills for Agentic Image Restoration
Jie Shao, Shengkai Hu, Xu Zhang +4
This paper studies agentic image restoration, in which multimodal agents coordinate specialized restoration tools to recover images affected by complex degradations. Existing resto…
FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection
Jun Wan, Jiwei Hu, Shengkai Hu +1
Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD methods still struggle unde…
FreqFLD: Towards All-in-One Facial Landmark Detection via Frequency Modulation
Shun Ren, Kaijie Jin, Shengkai Hu +5
Recent progress in deep learning has significantly advanced facial landmark detection. However, most existing methods process features in a spatial-domain manner under a dataset-sp…
SpikeRestormer: Towards Energy-Efficient All-in-One Image Restoration via Unified Event Reasoning
Shengkai Hu, Jie Shao, Jiaqi Ma +5
ANN-based All-in-One image restoration (AiOIR) unifies diverse degradation handling but incurs high computational costs, limiting its real-time deployment. While Spiking Neural Net…
EvoIR: Towards All-in-One Image Restoration via Evolutionary Frequency Modulation
Jiaqi Ma, Shengkai Hu, Xu Zhang +4
All-in-One Image Restoration (AiOIR) tasks often involve diverse degradation that require robust and versatile strategies. However, most existing approaches typically lack explicit…
ClusIR: Towards Cluster-Guided All-in-One Image Restoration
Shengkai Hu, Jiaqi Ma, Xu Zhang +3
All-in-One Image Restoration (AiOIR) aims to recover high-quality images from diverse degradations within a unified framework. However, existing methods often fail to explicitly mo…
Proto-Former: Unified Facial Landmark Detection by Prototype Transformer
Shengkai Hu, Haozhe Qi, Jun Wan +4
Recent advances in deep learning have significantly improved facial landmark detection. However, existing facial landmark detection datasets often define different numbers of landm…