13 citations · 15 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
HonestFace: Towards Honest Face Restoration with One-Step Diffusion Model
Jingkai Wang, Wu Miao, Jue Gong +5
Face restoration has achieved significant advancements through the years of development. However, maintaining high fidelity and authenticity while avoiding artifacts remains challe…
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…
NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Results
Zheng Chen, Kai Liu, Jue Gong +108
This paper presents the NTIRE 2025 image super-resolution (4) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025. The challenge aims to r…
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…