Cover Image

AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mao, Jiawei, Yang, Yu, Yin, Xuesong, Shao, Ling, Tang, Hao
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance
by: Mao, Jiawei, et al.
Published: (2024)

Neural Degradation Representation Learning for All-In-One Image Restoration
by: Yao, Mingde, et al.
Published: (2023)

Dynamic Degradation Decomposition Network for All-in-One Image Restoration
by: Wang, Huiqiang, et al.
Published: (2025)

Unifying Heterogeneous Degradations: Uncertainty-Aware Diffusion Bridge Model for All-in-One Image Restoration
by: Tu, Luwei, et al.
Published: (2026)

All-in-One Image Compression and Restoration
by: Zeng, Huimin, et al.
Published: (2025)

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

All-in-One Video Restoration under Smoothly Evolving Unknown Weather Degradations
by: Li, Wenrui, et al.
Published: (2026)

Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restoration
by: Zhang, Xu, et al.
Published: (2024)

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

Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image Restoration
by: Wu, Gang, et al.
Published: (2025)

Degradation-Aware All-in-One Image Restoration via Latent Prior Encoding
by: Sharif, S M A, et al.
Published: (2025)

Diffusion Once and Done: Degradation-Aware LoRA for Efficient All-in-One Image Restoration
by: Tang, Ni, et al.
Published: (2025)

Degradation Frequency Curve: An Explicit Frequency-Quantified Representation for All-in-One Image Restoration
by: Huang, Xinghua, et al.
Published: (2026)

Adaptive Blind All-in-One Image Restoration
by: Serrano-Lozano, David, et al.
Published: (2024)

OneRestore: A Universal Restoration Framework for Composite Degradation
by: Guo, Yu, et al.
Published: (2024)

MiM-DiT: MoE in MoE with Diffusion Transformers for All-in-One Image Restoration
by: Kong, Lingshun, et al.
Published: (2026)

GenDeg: Diffusion-based Degradation Synthesis for Generalizable All-In-One Image Restoration
by: Rajagopalan, Sudarshan, et al.
Published: (2024)

One Latent Space to Rule All Degradations: Unifying Restoration Knowledge for Image Fusion
by: Ma, Haolong, et al.
Published: (2025)

Gradient as Conditions: Rethinking HOG for All-in-one Image Restoration
by: Wu, Jiawei, et al.
Published: (2025)

HAIR: Hypernetworks-based All-in-One Image Restoration
by: Cao, Jin, et al.
Published: (2024)

Accurate Forgetting for All-in-One Image Restoration Model
by: Su, Xin, et al.
Published: (2024)

Degradation-Aware Feature Perturbation for All-in-One Image Restoration
by: Tian, Xiangpeng, et al.
Published: (2025)

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

RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration
by: Rajagopalan, Sudarshan, et al.
Published: (2025)

All-In-One Medical Image Restoration via Task-Adaptive Routing
by: Yang, Zhiwen, et al.
Published: (2024)

Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
by: Luo, Wenyang, et al.
Published: (2025)

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

Prompt-based Ingredient-Oriented All-in-One Image Restoration
by: Gao, Hu, et al.
Published: (2023)

UniLDiff: Unlocking the Power of Diffusion Priors for All-in-One Image Restoration
by: Cheng, Zihan, et al.
Published: (2025)

Learning Dual Transformers for All-In-One Image Restoration from a Frequency Perspective
by: Chu, Jie, et al.
Published: (2024)

PhyDAE: Physics-Guided Degradation-Adaptive Experts for All-in-One Remote Sensing Image Restoration
by: Dong, Zhe, et al.
Published: (2025)

Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image Restoration
by: Yu, Xiaoyan, et al.
Published: (2024)

TANet: Triplet Attention Network for All-In-One Adverse Weather Image Restoration
by: Wang, Hsing-Hua, et al.
Published: (2024)

Unleashing Degradation-Carrying Features in Symmetric U-Net: Simpler and Stronger Baselines for All-in-One Image Restoration
by: Jiao, Wenlong, et al.
Published: (2025)

From Controlled Scenarios to Real-World: Cross-Domain Degradation Pattern Matching for All-in-One Image Restoration
by: Fan, Junyu, et al.
Published: (2025)

Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image Restoration
by: Dudhane, Akshay, et al.
Published: (2024)

Unified-Width Adaptive Dynamic Network for All-In-One Image Restoration
by: Xu, Yimin, et al.
Published: (2024)

AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusion
by: Jiang, Yitong, et al.
Published: (2023)

UniUIR: Considering Underwater Image Restoration as An All-in-One Learner
by: Zhang, Xu, et al.
Published: (2025)

ClusIR: Towards Cluster-Guided All-in-One Image Restoration
by: Hu, Shengkai, et al.
Published: (2025)