Restormer: Efficient Transformer for High-Resolution Image Restoration
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- Type
- preprint
- Published
- 2021-11-18
- Cited by
- 4,401
- References
- 109
- Access
- Open access
- OpenAlex
- https://openalex.org/W3212228063
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:244346144
Keywords
Deblurring, Computer science, Artificial intelligence, Image restoration, Transformer
References
- Color demosaicking by local directional interpolation and nonlocal adaptive thresholding
- Just noticeable defocus blur detection and estimation
- Single image super-resolution from transformed self-exemplars
- Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
- Deep photo: model-based photograph enhancement and viewing
- A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
- Anchored Neighborhood Regression for Fast Example-Based Super-Resolution
- Nonparametric Blind Super-resolution
- Unnatural L0 Sparse Representation for Natural Image Deblurring
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
- Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
- Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal
- SGDR: Stochastic Gradient Descent with Warm Restarts
- Deep Joint Rain Detection and Removal from a Single Image
- Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring
- Image De-Raining Using a Conditional Generative Adversarial Network
- Learning Deep CNN Denoiser Prior for Image Restoration
- Benchmarking Denoising Algorithms with Real Photographs
- Enhanced Deep Residual Networks for Single Image Super-Resolution
- Removing Rain from Single Images via a Deep Detail Network
Cited by
- Optimization-Inspired Learning With Architecture Augmentations and Control Mechanisms for Low-Level Vision
- Transformers in Vision: A Survey
- Synergy between Semantic Segmentation and Image Denoising via Alternate Boosting
- NTIRE 2022 Challenge on Perceptual Image Quality Assessment
- Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration
- Self-supervised Video Transformer
- Adaptive Cross-Layer Attention for Image Restoration
- Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction
- Efficient Long-Range Attention Network for Image Super-resolution
- RFormer: Transformer-Based Generative Adversarial Network for Real Fundus Image Restoration on a New Clinical Benchmark
- TAPE: Task-Agnostic Prior Embedding for Image Restoration
- Simple Baselines for Image Restoration
- Learning Enriched Features for Fast Image Restoration and Enhancement
- NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
- Progressive Training of A Two-Stage Framework for Video Restoration
- MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
- MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction
- Self-Calibrated Efficient Transformer for Lightweight Super-Resolution
- Learning Dual-Pixel Alignment for Defocus Deblurring
- Coarse-to-Fine Video Denoising with Dual-Stage Spatial-Channel Transformer
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