Copertina

Learning Dual Transformers for All-In-One Image Restoration from a Frequency Perspective

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chu, Jie, Su, Tong, Liu, Pei, Wu, Yunpeng, Zhang, Le, Shi, Zenglin, Wang, Meng
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Densely Distilling Cumulative Knowledge for Continual Learning
di: Shi, Zenglin, et al.
Pubblicazione: (2024)

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

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

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

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

Review Learning: Advancing All-in-One Ultra-High-Definition Image Restoration Training Method
di: Su, Xin, et al.
Pubblicazione: (2024)

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

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

Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal
di: Liao, Rongxin, et al.
Pubblicazione: (2025)

EvoIR: Towards All-in-One Image Restoration via Evolutionary Frequency Modulation
di: Ma, Jiaqi, et al.
Pubblicazione: (2025)

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

Boosting All-in-One Image Restoration via Self-Improved Privilege Learning
di: Wu, Gang, et al.
Pubblicazione: (2025)

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

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

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

AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
di: Cui, Yuning, et al.
Pubblicazione: (2024)

DRNet: All-in-One Image Restoration via Prior-Guided Dynamic Reparameterization
di: Li, Ao, et al.
Pubblicazione: (2026)

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

FAPE-IR: Frequency-Aware Planning and Execution Framework for All-in-One Image Restoration
di: Liu, Jingren, et al.
Pubblicazione: (2025)

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

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

RAM++: Robust Representation Learning via Adaptive Mask for All-in-One Image Restoration
di: Zhang, Zilong, et al.
Pubblicazione: (2025)

Dual Prompting Image Restoration with Diffusion Transformers
di: Kong, Dehong, et al.
Pubblicazione: (2025)

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

Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration
di: Zhou, Shihao, et al.
Pubblicazione: (2024)

SLER-IR: Spherical Layer-wise Expert Routing for All-in-One Image Restoration
di: Shurui, Peng, et al.
Pubblicazione: (2026)

Leveraging Multimodal Large Language Models for All-in-One Image Restoration via a Mixture of Frequency Experts
di: Lee, Eunho, et al.
Pubblicazione: (2026)

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

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

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

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

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

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

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

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

ClearAIR: A Human-Visual-Perception-Inspired All-in-One Image Restoration
di: Zhang, Xu, et al.
Pubblicazione: (2026)

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

M2Restore: Mixture-of-Experts-based Mamba-CNN Fusion Framework for All-in-One Image Restoration
di: Wang, Yongzhen, et al.
Pubblicazione: (2025)

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

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