1 citations · 1 across the 11 of their papers we have counts for
15 papers
Two Halves are More than One: Phase-wise Velocity Distillation for Fast and High-Quality Image Generation
Zhen Guo, Rongyuan Wu, Qiaosi Yi +3
Recent diffusion-based image generation backbones have grown substantially in scale, making the network inference cost increase rapidly. While diffusion distillation techniques can…
LDM-is-AE: Latent Diffusion Model is an Auto-Encoder for End-to-End Image Generation
Zhengqiang Zhang, Lingchen Sun, Rongyuan Wu +4
Latent Diffusion Models (LDMs) typically adopt a two-stage pipeline: an auto-encoder (AE) is first pre-trained to define a latent space, then a diffusion model is trained to perfor…
PixRestore: Unified Image Restoration via Pixel Diffusion Transformer
Lingchen Sun, Rongyuan Wu, Xiangtao Kong +6
Unified image restoration (UIR) aims to recover high-quality (HQ) content from low-quality (LQ) images with different degradations using a single model. Most recent methods adapt l…
Text-Vision Co-Instructed Image Editing
Chenxi Xie, Yuhui Wu, Qiaosi Yi +1
Existing image editing methods can be generally categorized into textual instruction-based and visual prompt-based ones. Textual instructions are semantically expressive, but are l…
NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
Xin Li, Yeying Jin, Suhang Yao +95
This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…
LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results
Xiang Chen, Hao Li, Jiangxin Dong +54
This paper presents a review for the LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aimed to advance research on real-world all-in-one image restoration…
GDPO-SR: Group Direct Preference Optimization for One-Step Generative Image Super-Resolution
Qiaosi Yi, Shuai Li, Rongyuan Wu +3
Recently, reinforcement learning (RL) has been employed for improving generative image super-resolution (ISR) performance. However, the current efforts are focused on multi-step ge…
CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning
Yuhui Wu, Chenxi Xie, Ruibin Li +3
Image editing has achieved impressive results with the development of large-scale generative models. However, existing models mainly focus on the editing effects of intended object…
DPO-SR: Direct Perceptual Preference Optimization for Real-World Image Super-Resolution
Rongyuan Wu, Lingchen Sun, Zhengqiang Zhang +5
Benefiting from pre-trained text-to-image (T2I) diffusion models, real-world image super-resolution (Real-ISR) methods can synthesize rich and realistic details. However, due to th…
Fine-structure Preserved Real-world Image Super-resolution via Transfer VAE Training
Qiaosi Yi, Shuai Li, Rongyuan Wu +3
Impressive results on real-world image super-resolution (Real-ISR) have been achieved by employing pre-trained stable diffusion (SD) models. However, one critical issue of such met…
DNAEdit: Direct Noise Alignment for Text-Guided Rectified Flow Editing
Chenxi Xie, Minghan Li, Shuai Li +3
Leveraging the powerful generation capability of large-scale pretrained text-to-image models, training-free methods have demonstrated impressive image editing results. Conventional…
NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge
Jie Liang, Radu Timofte, Qiaosi Yi +7
In this paper, we present a comprehensive overview of the NTIRE 2025 challenge on the 2nd Restore Any Image Model (RAIM) in the Wild. This challenge established a new benchmark for…
NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
Xin Li, Yeying Jin, Xin Jin +134
This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images. This challenge received a wide range of impressive solutions, which are devel…
Pixel-level and Semantic-level Adjustable Super-resolution: A Dual-LoRA Approach
Lingchen Sun, Rongyuan Wu, Zhiyuan Ma +3
Diffusion prior-based methods have shown impressive results in real-world image super-resolution (SR). However, most existing methods entangle pixel-level and semantic-level SR obj…
NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge
Jie Liang, Radu Timofte, Qiaosi Yi +6
In this paper, we review the NTIRE 2024 challenge on Restore Any Image Model (RAIM) in the Wild. The RAIM challenge constructed a benchmark for image restoration in the wild, inclu…