Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration
Fuente:
arXiv
Saved in:
| Main Authors: | Deng, Junyuan, Wu, Xinyi, Yang, Yongxing, Zhu, Congchao, Wang, Song, Wu, Zhenyao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Are Conditional Latent Diffusion Models Effective for Image Restoration?
by: Yuan, Yunchen, et al.
Published: (2024)
by: Yuan, Yunchen, et al.
Published: (2024)
Restoring Initial Noise Sensitivity in Text-to-Image Distillation via Geometric Alignment
by: Huang, Huayang, et al.
Published: (2026)
by: Huang, Huayang, et al.
Published: (2026)
Streamline Without Sacrifice -- Squeeze out Computation Redundancy in LMM
by: Wu, Penghao, et al.
Published: (2025)
by: Wu, Penghao, et al.
Published: (2025)
Restore Text First, Enhance Image Later: Two-Stage Scene Text Image Super-Resolution with Glyph Structure Guidance
by: Luo, Minxing, et al.
Published: (2025)
by: Luo, Minxing, et al.
Published: (2025)
Diffusion Restoration Adapter for Real-World Image Restoration
by: Liang, Hanbang, et al.
Published: (2025)
by: Liang, Hanbang, et al.
Published: (2025)
TurboFill: Adapting Few-step Text-to-image Model for Fast Image Inpainting
by: Xie, Liangbin, et al.
Published: (2025)
by: Xie, Liangbin, et al.
Published: (2025)
Gradient as Conditions: Rethinking HOG for All-in-one Image Restoration
by: Wu, Jiawei, et al.
Published: (2025)
by: Wu, Jiawei, 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)
by: Qin, Chu-Jie, et al.
Published: (2024)
How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization?
by: Dong, Jiahua, et al.
Published: (2024)
by: Dong, Jiahua, et al.
Published: (2024)
Multi-Scale Representation Learning for Image Restoration with State-Space Model
by: He, Yuhong, et al.
Published: (2024)
by: He, Yuhong, et al.
Published: (2024)
Equivariant Sampling for Improving Diffusion Model-based Image Restoration
by: Wu, Chenxu, et al.
Published: (2025)
by: Wu, Chenxu, et al.
Published: (2025)
TextRegion: Text-Aligned Region Tokens from Frozen Image-Text Models
by: Xiao, Yao, et al.
Published: (2025)
by: Xiao, Yao, et al.
Published: (2025)
A Preliminary Study on GPT-Image Generation Model for Image Restoration
by: Yang, Hao, et al.
Published: (2025)
by: Yang, Hao, et al.
Published: (2025)
360Recon: An Accurate Reconstruction Method Based on Depth Fusion from 360 Images
by: Yan, Zhongmiao, et al.
Published: (2024)
by: Yan, Zhongmiao, et al.
Published: (2024)
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
by: Zheng, Dian, et al.
Published: (2024)
by: Zheng, Dian, et al.
Published: (2024)
Task-Guided Prompting for Unified Remote Sensing Image Restoration
by: Huang, Wenli, et al.
Published: (2026)
by: Huang, Wenli, et al.
Published: (2026)
CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration
by: Deng, Rui, et al.
Published: (2024)
by: Deng, Rui, et al.
Published: (2024)
FlowInOne:Unifying Multimodal Generation as Image-in, Image-out Flow Matching
by: Yi, Junchao, et al.
Published: (2026)
by: Yi, Junchao, et al.
Published: (2026)
When To Adapt? Adapting the Model or Data in Federated Medical Imaging
by: Shiranthika, Chamani, et al.
Published: (2026)
by: Shiranthika, Chamani, et al.
Published: (2026)
Bridge the Gap between SNN and ANN for Image Restoration
by: Su, Xin, et al.
Published: (2025)
by: Su, Xin, et al.
Published: (2025)
Adapting Foundation Models for Few-Shot Medical Image Segmentation: Actively and Sequentially
by: Yang, Jingyun, et al.
Published: (2025)
by: Yang, Jingyun, et al.
Published: (2025)
Vision-Language Model Guided Image Restoration
by: Yang, Cuixin, et al.
Published: (2025)
by: Yang, Cuixin, et al.
Published: (2025)
Beyond Pixels: Text Enhances Generalization in Real-World Image Restoration
by: Sun, Haoze, et al.
Published: (2024)
by: Sun, Haoze, et al.
Published: (2024)
TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt
by: Wu, Xiangyu, et al.
Published: (2024)
by: Wu, Xiangyu, et al.
Published: (2024)
Adapting Segment Anything Model for Change Detection in HR Remote Sensing Images
by: Ding, Lei, et al.
Published: (2023)
by: Ding, Lei, et al.
Published: (2023)
Correlation Matching Transformation Transformers for UHD Image Restoration
by: Wang, Cong, et al.
Published: (2024)
by: Wang, Cong, et al.
Published: (2024)
Progressive Split Mamba: Effective State Space Modelling for Image Restoration
by: Hassanin, Mohammed, et al.
Published: (2026)
by: Hassanin, Mohammed, et al.
Published: (2026)
MixNet: Efficient Global Modeling for Ultra-High-Definition Image Restoration
by: Wu, Chen, et al.
Published: (2024)
by: Wu, Chen, et al.
Published: (2024)
Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
by: Wu, Gang, et al.
Published: (2023)
by: Wu, Gang, et al.
Published: (2023)
Origin Identification for Text-Guided Image-to-Image Diffusion Models
by: Wang, Wenhao, et al.
Published: (2025)
by: Wang, Wenhao, et al.
Published: (2025)
SketchTriplet: Self-Supervised Scenarized Sketch-Text-Image Triplet Generation
by: Wu, Zhenbei, et al.
Published: (2024)
by: Wu, Zhenbei, et al.
Published: (2024)
RealRestorer: Towards Generalizable Real-World Image Restoration with Large-Scale Image Editing Models
by: Yang, Yufeng, et al.
Published: (2026)
by: Yang, Yufeng, et al.
Published: (2026)
Residual Diffusion Bridge Model for Image Restoration
by: Wang, Hebaixu, et al.
Published: (2025)
by: Wang, Hebaixu, et al.
Published: (2025)
Distribution-aware Dataset Distillation for Efficient Image Restoration
by: Zheng, Zhuoran, et al.
Published: (2025)
by: Zheng, Zhuoran, 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)
by: Huang, Xinghua, et al.
Published: (2026)
Dynamic Degradation Decomposition Network for All-in-One Image Restoration
by: Wang, Huiqiang, et al.
Published: (2025)
by: Wang, Huiqiang, et al.
Published: (2025)
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
by: Wu, Junde, et al.
Published: (2023)
by: Wu, Junde, et al.
Published: (2023)
TSFormer: A Robust Framework for Efficient UHD Image Restoration
by: Su, Xin, et al.
Published: (2024)
by: Su, Xin, et al.
Published: (2024)
Language-Image Alignment with Fixed Text Encoders
by: Yang, Jingfeng, et al.
Published: (2025)
by: Yang, Jingfeng, et al.
Published: (2025)
Efficient Degradation-aware Any Image Restoration
by: Zamfir, Eduard, et al.
Published: (2024)
by: Zamfir, Eduard, et al.
Published: (2024)
Similar Items
-
Are Conditional Latent Diffusion Models Effective for Image Restoration?
by: Yuan, Yunchen, et al.
Published: (2024) -
Restoring Initial Noise Sensitivity in Text-to-Image Distillation via Geometric Alignment
by: Huang, Huayang, et al.
Published: (2026) -
Streamline Without Sacrifice -- Squeeze out Computation Redundancy in LMM
by: Wu, Penghao, et al.
Published: (2025) -
Restore Text First, Enhance Image Later: Two-Stage Scene Text Image Super-Resolution with Glyph Structure Guidance
by: Luo, Minxing, et al.
Published: (2025) -
Diffusion Restoration Adapter for Real-World Image Restoration
by: Liang, Hanbang, et al.
Published: (2025)