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All-Weather Image Restoration (AWIR) under adverse weather conditions is a challenging task due to the presence of different types of degradations.
Vision Transformers for Single Image Dehazing
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An image is worth 16x16 words: Transformers for image recognition at scale
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Gaussian error linear units (gelus)
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Attention is all you need
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Deep Joint Rain Detection and Removal from a Single Image
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DesnowNet: Context-Aware Deep Network for Snow Removal
Liu, Y.-F.; Jaw, D.-W.; Huang, S.-C.; and Hwang, J.-N. 2018 · 2018
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Densely Connected Pyramid Dehazing Network
Zhang, H.; and Patel, V. M. 2018 · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
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Semantic Understanding of Foggy Scenes with Purely Synthetic Data
Hahner, M.; Dai, D.; Sakaridis, C.; Zaech, J.-N.; and Gool, L. V. 2019 · 2019
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Benchmarking Single-Image Dehazing and Beyond
Li, B.; Ren, W.; Fu, D.; Tao, D.; Feng, D.; Zeng, W.; and Wang, Z. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
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Spatial Attentive Single-Image Deraining With a High Quality Real Rain Dataset
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Semi-Supervised Transfer Learning for Image Rain Removal
Wei, W.; Meng, D.; Zhao, Q.; Xu, Z.; and Wu, Y. 2019 · 2019
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Language Models Are Few-Shot Learners
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End-to-end object detection with transformers
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JSTASR: Joint Size and Transparency-Aware Snow Removal Algorithm Based on Modified Partial Convolution and Veiling Effect Removal
Chen, W.-T.; Fang, H.-Y.; Ding, J.-J.; Tsai, C.-C.; and Kuo, S.-Y. 2020 · 2020
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Momentum Contrast for Unsupervised Visual Representation Learning
He, K.; Fan, H.; Wu, Y.; Xie, S.; and Girshick, R. 2020 · 2020
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All in One Bad Weather Removal Using Architectural Search
Li, R.; Tan, R. T.; and Cheong, L.-F. 2020 · 2020
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Uformer: A General U-Shaped Transformer for Image Restoration
Wang, Z.; Cun, X.; Bao, J.; Zhou, W.; Liu, J.; and Li, H. 2022 · 2022
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Restormer: Efficient Transformer for High-Resolution Image Restoration
Zamir, S. W.; Arora, A.; Khan, S.; Hayat, M.; Khan, F. S.; and Yang, M.-H. 2022 · 2022
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Tip-adapter: Training-free adaption of clip for few-shot classification
Zhang, R.; Zhang, W.; Fang, R.; Gao, P.; Li, K.; Dai, J.; Qiao, Y.; and Li, H. 2022 · 2022
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TextIR: A Simple Framework for Text-based Editable Image Restoration
Bai, Y.; Wang, C.; Xie, S.; Dong, C.; Yuan, C.; and Wang, Z. 2023 · 2023
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Unifying image processing as visual prompting question answering
Liu, Y.; Chen, X.; Ma, X.; Wang, X.; Zhou, J.; Qiao, Y.; and Dong, C. 2023 · 2023
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Pix2seq: A language modeling framework for object detection
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Open-vocabulary object detection via vision and language knowledge distillation
Gu, X.; Lin, T.-Y.; Kuo, W.; and Cui, Y. 2021 · 2021
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SwinIR: Image Restoration Using Swin Transformer
Liang, J.; Cao, J.; Sun, G.; Zhang, K.; Van Gool, L.; and Timofte, R. 2021 · 2021
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Removing raindrops and rain streaks in one go
Quan, R.; Yu, X.; Liang, Y.; and Yang, Y. 2021 · 2021
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Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
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How much can clip benefit vision-and-language tasks?
Shen, S.; Li, L. H.; Tan, H.; Bansal, M.; Rohrbach, A.; Chang, K.-W.; Yao, Z.; and Keutzer, K. 2021 · 2021
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Multi-Stage Progressive Image Restoration
Zamir, S. W.; Arora, A.; Khan, S.; Hayat, M.; Khan, F. S.; Yang, M.-H.; and Shao, L. 2021 · 2021
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Controlling vision-language models for universal image restoration
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Restoring vision in adverse weather conditions with patch-based denoising diffusion models
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All-in-One Image Restoration for Unknown Degradations Using Adaptive Discriminative Filters for Specific Degradations
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Multi-weather Image Restoration via Domain Translation
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Textual Prompt Guided Image Restoration
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Learning Weather-General and Weather-Specific Features for Image Restoration Under Multiple Adverse Weather Conditions
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Multimodal Prompt Perceiver: Empower Adaptiveness Generalizability and Fidelity for All-in-One Image Restoration
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PromptIR: Prompting for All-in-One Image Restoration
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Boosting Image Restoration via Priors from Pre-trained Models
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Distilling Semantic Priors from SAM to Efficient Image Restoration Models
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Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
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