54 citations · 57 across the 15 of their papers we have counts for
16 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…
MMG2Skill: Can Agents Distill In-the-Wild Guides into Self-Evolving Skills?
Xinyu Che, Junqi Xiong, Yunfei Ge +9
Abundant procedural knowledge on the Web holds great potential for helping agents solve long-horizon tasks. However, such knowledge is often multimodal, heterogeneous, noisy, and i…
WebCompass: Towards Multimodal Web Coding Evaluation for Code Language Models
Xinping Lei, Xinyu Che, Junqi Xiong +16
Large language models are rapidly evolving into interactive coding agents capable of end-to-end web coding, yet existing benchmarks evaluate only narrow slices of this capability,…
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…
ShiftLUT: Spatial Shift Enhanced Look-Up Tables for Efficient Image Restoration
Xiaolong Zeng, Yitong Yu, Shiyao Xiong +4
Look-Up Table based methods have emerged as a promising direction for efficient image restoration tasks. Recent LUT-based methods focus on improving their performance by expanding…
InstantViR: Real-Time Video Inverse Problem Solver with Distilled Diffusion Prior
Weimin Bai, Suzhe Xu, Yiwei Ren +4
Video inverse problems are fundamental to streaming, telepresence, and AR/VR, where high perceptual quality must coexist with tight latency constraints. Diffusion-based priors curr…
HPGN: Hybrid Priors-Guided Network for Compressed Low-Light Image Enhancement
Hantang Li, Qiang Zhu, Xiandong Meng +3
In practical applications, low-light images are often compressed for efficient storage and transmission. Most existing methods disregard compression artifacts removal or hardly est…
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…
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 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…