54 citations · 58 across the 21 of their papers we have counts for
21 papers
LPM: Industrial-Scale Generative Video Restoration
Bichuan Zhu, Fulin Li, Jiachao Gong +14
We present the Large Processing Model (LPM), a diffusion-based generative framework for photorealistic video restoration under complex, in-the-wild degradations. To our knowledge,…
Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution
Hongbo Wang, Huaibo Huang, Pin Wang +3
Generative priors in Image Super-Resolution (SR) often compromise faithful restoration, we attribute this limitation to a fundamental spectral misalignment between isotropic object…
Pioneering Perceptual Video Fluency Assessment: A Novel Task with Benchmark Dataset and Baseline
Qizhi Xie, Kun Yuan, Yunpeng Qu +3
Accurately estimating humans' subjective feedback on video fluency, e.g., motion consistency and frame continuity, is crucial for various applications like streaming and gaming. Ye…
Tuning Real-World Image Restoration at Inference: A Test-Time Scaling Paradigm for Flow Matching Models
Purui Bai, Junxian Duan, Pin Wang +4
Although diffusion-based real-world image restoration (Real-IR) has achieved remarkable progress, efficiently leveraging ultra-large-scale pre-trained text-to-image (T2I) models an…
Versatile Recompression-Aware Perceptual Image Super-Resolution
Mingwei He, Tongda Xu, Xingtong Ge +3
Perceptual image super-resolution (SR) methods restore degraded images and produce sharp outputs. In practice, those outputs are usually recompressed for storage and transmission.…
Score2Instruct: Scaling Up Video Quality-Centric Instructions via Automated Dimension Scoring
Qizhi Xie, Kun Yuan, Yunpeng Qu +5
Classical video quality assessment methods generate a numerical score to judge a video's perceived visual fidelity and clarity. Yet, a score fails to describe the video's complex q…
Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling
Rui Qin, Qijie Wang, Ming Sun +3
Diffusion models have gained attention for their success in modeling complex distributions, achieving impressive perceptual quality in SR tasks. However, existing diffusion-based S…
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results
Xin Li, Kun Yuan, Bingchen Li +110
This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement. The challenge comprises two tracks: (i) Efficient Video Qualit…
KVQ: Boosting Video Quality Assessment via Saliency-guided Local Perception
Yunpeng Qu, Kun Yuan, Qizhi Xie +3
Video Quality Assessment (VQA), which intends to predict the perceptual quality of videos, has attracted increasing attention. Due to factors like motion blur or specific distortio…
Visual Autoregressive Modeling for Image Super-Resolution
Yunpeng Qu, Kun Yuan, Jinhua Hao +4
Image Super-Resolution (ISR) has seen significant progress with the introduction of remarkable generative models. However, challenges such as the trade-off issues between fidelity…
Plug-and-Play Tri-Branch Invertible Block for Image Rescaling
Jingwei Bao, Jinhua Hao, Pengcheng Xu +3
High-resolution (HR) images are commonly downscaled to low-resolution (LR) to reduce bandwidth, followed by upscaling to restore their original details. Recent advancements in imag…
OAPT: Offset-Aware Partition Transformer for Double JPEG Artifacts Removal
Qiao Mo, Yukang Ding, Jinhua Hao +5
Deep learning-based methods have shown remarkable performance in single JPEG artifacts removal task. However, existing methods tend to degrade on double JPEG images, which are prev…
A New Dataset and Framework for Real-World Blurred Images Super-Resolution
Rui Qin, Ming Sun, Chao Zhou +1
Recent Blind Image Super-Resolution (BSR) methods have shown proficiency in general images. However, we find that the efficacy of recent methods obviously diminishes when employed…
QPT V2: Masked Image Modeling Advances Visual Scoring
Qizhi Xie, Kun Yuan, Yunpeng Qu +4
Quality assessment and aesthetics assessment aim to evaluate the perceived quality and aesthetics of visual content. Current learning-based methods suffer greatly from the scarcity…
PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild
Kun Yuan, Hongbo Liu, Mading Li +6
Video quality assessment (VQA) is a challenging problem due to the numerous factors that can affect the perceptual quality of a video, \eg, content attractiveness, distortion type,…
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results
Xin Li, Kun Yuan, Yajing Pei +65
This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected da…
NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Results
Zheng Chen, Zongwei Wu, Eduard Zamfir +85
This paper reviews the NTIRE 2024 challenge on image super-resolution (4), highlighting the solutions proposed and the outcomes obtained. The challenge involves generating…
CasSR: Activating Image Power for Real-World Image Super-Resolution
Haolan Chen, Jinhua Hao, Kai Zhao +4
The objective of image super-resolution is to generate clean and high-resolution images from degraded versions. Recent advancements in diffusion modeling have led to the emergence…
CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancement
Qiang Zhu, Jinhua Hao, Yukang Ding +5
Recently, numerous approaches have achieved notable success in compressed video quality enhancement (VQE). However, these methods usually ignore the utilization of valuable coding…
XPSR: Cross-modal Priors for Diffusion-based Image Super-Resolution
Yunpeng Qu, Kun Yuan, Kai Zhao +4
Diffusion-based methods, endowed with a formidable generative prior, have received increasing attention in Image Super-Resolution (ISR) recently. However, as low-resolution (LR) im…
KVQ: Kwai Video Quality Assessment for Short-form Videos
Yiting Lu, Xin Li, Yajing Pei +6
Short-form UGC video platforms, like Kwai and TikTok, have been an emerging and irreplaceable mainstream media form, thriving on user-friendly engagement, and kaleidoscope creation…