6 papers
LCUDiff: Latent Capacity Upgrade Diffusion for Faithful Human Body Restoration
Jue Gong, Zihan Zhou, Jingkai Wang +4
Existing methods for restoring degraded human-centric images often struggle with insufficient fidelity, particularly in human body restoration (HBR). Recent diffusion-based restora…
Light Up Your Face: A Physically Consistent Dataset and Diffusion Model for Face Fill-Light Enhancement
Jue Gong, Zihan Zhou, Jingkai Wang +3
Face fill-light enhancement (FFE) brightens underexposed faces by adding virtual fill light while keeping the original scene illumination and background unchanged. Most face religh…
QuantFace: Efficient Quantization for Face Restoration
Jiatong Li, Libo Zhu, Haotong Qin +5
Diffusion models have been achieving remarkable performance in face restoration. However, the heavy computations hamper the widespread adoption of these models. In this work, we pr…
HAODiff: Human-Aware One-Step Diffusion via Dual-Prompt Guidance
Jue Gong, Tingyu Yang, Jingkai Wang +5
Human-centered images often suffer from severe generic degradation during transmission and are prone to human motion blur (HMB), making restoration challenging. Existing research l…
NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results
Zheng Chen, Jingkai Wang, Kai Liu +51
This paper provides a review of the NTIRE 2025 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on ge…
Human Body Restoration with One-Step Diffusion Model and A New Benchmark
Jue Gong, Jingkai Wang, Zheng Chen +4
Human body restoration, as a specific application of image restoration, is widely applied in practice and plays a vital role across diverse fields. However, thorough research remai…