activity
20232026
most citedUCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt

1 citations · 1 across the 21 of their papers we have counts for

collaborators

25 papers

cs.CV2026

UniDiffFusion: A Unified Diffusion Framework for Multi-Task and Degradation-Robust Image Fusion

Xingxin Xu, Siqi Zhao, Xin Li +3

General image fusion aims to integrate complementary information from multiple source images, but existing methods often rely on task-specific models and struggle to maintain robus…

eess.IV2026

ZeroGVC: Zero-Shot Generative Video Compression with Autoregressive Diffusion Priors

Yixin Gao, Xiaohan Pan, Lin Liu +3

Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existing approaches require addition…

cs.CV2026

ColorFLUX: A Structure-Color Decoupling Framework for Old Photo Colorization

Bingchen Li, Zhixin Wang, Fan Li +5

Old photos preserve invaluable historical memories, making their restoration and colorization highly desirable. While existing restoration models can address some degradation issue…

cs.CV2025

Diff-ICMH: Harmonizing Machine and Human Vision in Image Compression with Generative Prior

Ruoyu Feng, Yunpeng Qi, Jinming Liu +4

Image compression methods are usually optimized isolatedly for human perception or machine analysis tasks. We reveal fundamental commonalities between these objectives: preserving…

cs.CV2025

4DWorldBench: A Comprehensive Evaluation Framework for 3D/4D World Generation Models

Yiting Lu, Wei Luo, Peiyan Tu +8

World Generation Models are emerging as a cornerstone of next-generation multimodal intelligence systems. Unlike traditional 2D visual generation, World Models aim to construct rea…

cs.CV2025

Test-Time Preference Optimization for Image Restoration

Bingchen Li, Xin Li, Jiaqi Xu +4

Image restoration (IR) models are typically trained to recover high-quality images using L1 or LPIPS loss. To handle diverse unknown degradations, zero-shot IR methods have also be…

cs.CV2025

P-4DGS: Predictive 4D Gaussian Splatting with 90 Compression

Henan Wang, Hanxin Zhu, Xinliang Gong +3

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D sce…

cs.CV2025

Comp-X: On Defining an Interactive Learned Image Compression Paradigm With Expert-driven LLM Agent

Yixin Gao, Xin Li, Xiaohan Pan +7

We present Comp-X, the first intelligently interactive image compression paradigm empowered by the impressive reasoning capability of large language model (LLM) agent. Notably, com…

cs.CV2025

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4RTX 4090s

Xijun Wang, Xin Li, Bingchen Li +1

Diffusion models have significantly advanced video super-resolution (VSR) by enhancing perceptual quality, largely through elaborately designed temporal modeling to ensure inter-fr…

cs.SD2025

Sonic4D: Spatial Audio Generation for Immersive 4D Scene Exploration

Siyi Xie, Hanxin Zhu, Xinyi Chen +3

Recent advancements in 4D generation have demonstrated its remarkable capability in synthesizing photorealistic renderings of dynamic 3D scenes. However, despite achieving impressi…

cs.CV2025

Why Compress What You Can Generate? When GPT-4o Generation Ushers in Image Compression Fields

Yixin Gao, Xiaohan Pan, Xin Li +1

The rapid development of AIGC foundation models has revolutionized the paradigm of image compression, which paves the way for the abandonment of most pixel-level transform and codi…

cs.CV2025

Hybrid Agents for Image Restoration

Bingchen Li, Xin Li, Yiting Lu +1

Existing Image Restoration (IR) studies typically focus on task-specific or universal modes individually, relying on the mode selection of users and lacking the cooperation between…

cs.CV2025

Q&C: When Quantization Meets Cache in Efficient Image Generation

Xin Ding, Xin Li, Haotong Qin +1

Quantization and cache mechanisms are typically applied individually for efficient Diffusion Transformers (DiTs), each demonstrating notable potential for acceleration. However, th…

cs.CV2024

TIV-Diffusion: Towards Object-Centric Movement for Text-driven Image to Video Generation

Xingrui Wang, Xin Li, Yaosi Hu +4

Text-driven Image to Video Generation (TI2V) aims to generate controllable video given the first frame and corresponding textual description. The primary challenges of this task li…

eess.IV2024

UniMIC: Towards Universal Multi-modality Perceptual Image Compression

Yixin Gao, Xin Li, Xiaohan Pan +5

We present UniMIC, a universal multi-modality image compression framework, intending to unify the rate-distortion-perception (RDP) optimization for multiple image codecs simultaneo…

cs.CV2024

LossAgent: Towards Any Optimization Objectives for Image Processing with LLM Agents

Bingchen Li, Xin Li, Yiting Lu +1

We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e.g., image super-resolution and restoration, intending to achieve any customized optimizat…

cs.CV2024

Towards Defining an Efficient and Expandable File Format for AI-Generated Contents

Yixin Gao, Runsen Feng, Xin Li +2

Recently, AI-generated content (AIGC) has gained significant traction due to its powerful creation capability. However, the storage and transmission of large amounts of high-qualit…

cs.CV2024

MambaCSR: Dual-Interleaved Scanning for Compressed Image Super-Resolution With SSMs

Yulin Ren, Xin Li, Mengxi Guo +3

We present MambaCSR, a simple but effective framework based on Mamba for the challenging compressed image super-resolution (CSR) task. Particularly, the scanning strategies of Mamb…

cs.CV2024★ 1 cited

UCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt

Xin Li, Bingchen Li, Yeying Jin +4

Compressed Image Super-resolution (CSR) aims to simultaneously super-resolve the compressed images and tackle the challenging hybrid distortions caused by compression. However, exi…

eess.IV2024

MoE-DiffIR: Task-customized Diffusion Priors for Universal Compressed Image Restoration

Yulin Ren, Xin Li, Bingchen Li +5

We present MoE-DiffIR, an innovative universal compressed image restoration (CIR) method with task-customized diffusion priors. This intends to handle two pivotal challenges in the…

cs.CV2024

CoNo: Consistency Noise Injection for Tuning-free Long Video Diffusion

Xingrui Wang, Xin Li, Zhibo Chen

Tuning-free long video diffusion has been proposed to generate extended-duration videos with enriched content by reusing the knowledge from pre-trained short video diffusion model…

cs.CV2024

PromptCIR: Blind Compressed Image Restoration with Prompt Learning

Bingchen Li, Xin Li, Yiting Lu +5

Blind Compressed Image Restoration (CIR) has garnered significant attention due to its practical applications. It aims to mitigate compression artifacts caused by unknown quality f…

cs.CV2024

Is Vanilla MLP in Neural Radiance Field Enough for Few-shot View Synthesis?

Hanxin Zhu, Tianyu He, Xin Li +2

Neural Radiance Field (NeRF) has achieved superior performance for novel view synthesis by modeling the scene with a Multi-Layer Perception (MLP) and a volume rendering procedure,…

eess.IV2024

SeD: Semantic-Aware Discriminator for Image Super-Resolution

Bingchen Li, Xin Li, Hanxin Zhu +4

Generative Adversarial Networks (GANs) have been widely used to recover vivid textures in image super-resolution (SR) tasks. In particular, one discriminator is utilized to enable…