:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Sun, Weixiong, Yin, Xiang, Dong, Chao
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	https://arxiv.org/abs/2604.03061
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restoration
di: Dong, Guanglu, et al.
Pubblicazione: (2026)

Chain-of-Restoration: Multi-Task Image Restoration Models are Zero-Shot Step-by-Step Universal Image Restorers
di: Cao, Jin, et al.
Pubblicazione: (2024)

Reverse Convolution and Its Applications to Image Restoration
di: Huang, Xuhong, et al.
Pubblicazione: (2025)

Divide and Restore: A Modular Task-Decoupled Framework for Universal Image Restoration
di: Wiekiera, Joanna, et al.
Pubblicazione: (2026)

HAT: Hybrid Attention Transformer for Image Restoration
di: Chen, Xiangyu, et al.
Pubblicazione: (2023)

An Intelligent Agentic System for Complex Image Restoration Problems
di: Zhu, Kaiwen, et al.
Pubblicazione: (2024)

NanoSD: Edge Efficient Foundation Model for Real Time Image Restoration
di: Sanyal, Subhajit, et al.
Pubblicazione: (2026)

Vision-Language Model Guided Image Restoration
di: Yang, Cuixin, et al.
Pubblicazione: (2025)

RealRestorer: Towards Generalizable Real-World Image Restoration with Large-Scale Image Editing Models
di: Yang, Yufeng, et al.
Pubblicazione: (2026)

InstructRestore: Region-Customized Image Restoration with Human Instructions
di: Liu, Shuaizheng, et al.
Pubblicazione: (2025)

Controlling Vision-Language Models for Multi-Task Image Restoration
di: Luo, Ziwei, et al.
Pubblicazione: (2023)

AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations
di: Mao, Jiawei, et al.
Pubblicazione: (2024)

How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practices
di: Yin, Xiang, et al.
Pubblicazione: (2026)

GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity
di: Cao, Shuo, et al.
Pubblicazione: (2024)

A Preliminary Exploration Towards General Image Restoration
di: Kong, Xiangtao, et al.
Pubblicazione: (2024)

Exploiting Diffusion Prior for Task-driven Image Restoration
di: Kim, Jaeha, et al.
Pubblicazione: (2025)

Harnessing Diffusion-Yielded Score Priors for Image Restoration
di: Lin, Xinqi, et al.
Pubblicazione: (2025)

An Efficient and Mixed Heterogeneous Model for Image Restoration
di: Gu, Yubin, et al.
Pubblicazione: (2025)

Continual Learning-Based Unified Model for Unpaired Image Restoration Tasks
di: Kartheek, Kotha, et al.
Pubblicazione: (2025)

Restore Anything with Masks: Leveraging Mask Image Modeling for Blind All-in-One Image Restoration
di: Qin, Chu-Jie, et al.
Pubblicazione: (2024)

FoundIR-v2: Optimizing Pre-Training Data Mixtures for Image Restoration Foundation Model
di: Chen, Xiang, et al.
Pubblicazione: (2025)

Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy
di: Kong, Xiangtao, et al.
Pubblicazione: (2024)

Diffusion Restoration Adapter for Real-World Image Restoration
di: Liang, Hanbang, et al.
Pubblicazione: (2025)

Invert2Restore: Zero-Shot Degradation-Blind Image Restoration
di: Chihaoui, Hamadi, et al.
Pubblicazione: (2025)

Image Restoration via Primal Dual Hybrid Gradient and Flow Generative Model
di: Li, Ji, et al.
Pubblicazione: (2025)

Complexity Experts are Task-Discriminative Learners for Any Image Restoration
di: Zamfir, Eduard, et al.
Pubblicazione: (2024)

TDiR: Transformer based Diffusion for Image Restoration Tasks
di: Anwar, Abbas, et al.
Pubblicazione: (2025)

Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restoration
di: Tang, Xiaole, et al.
Pubblicazione: (2024)

Training Neural Networks on RAW and HDR Images for Restoration Tasks
di: Ke, Andrew Yanzhe, et al.
Pubblicazione: (2023)

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration
di: Li, Hao, et al.
Pubblicazione: (2024)

From Physical Degradation Models to Task-Aware All-in-One Image Restoration
di: Gao, Hu, et al.
Pubblicazione: (2026)

Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
di: Wu, Gang, et al.
Pubblicazione: (2023)

Learning Continuous Wasserstein Barycenter Space for Generalized All-in-One Image Restoration
di: Tang, Xiaole, et al.
Pubblicazione: (2026)

WaveDM: Wavelet-Based Diffusion Models for Image Restoration
di: Huang, Yi, et al.
Pubblicazione: (2023)

Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
di: Yu, Fanghua, et al.
Pubblicazione: (2024)

Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
di: Tang, Xiaole, et al.
Pubblicazione: (2024)

UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularity
di: Lin, Jingbo, et al.
Pubblicazione: (2024)

Residual Diffusion Bridge Model for Image Restoration
di: Wang, Hebaixu, et al.
Pubblicazione: (2025)

TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration
di: Yang, Zhiwen, et al.
Pubblicazione: (2025)

Pruning Overparameterized Multi-Task Networks for Degraded Web Image Restoration
di: Katraouras, Thomas, et al.
Pubblicazione: (2025)