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Learning Enriched Features for Fast Image Restoration and Enhancement
TPAMI 2022
A novel feature extraction model that obtains a complementary set of features across multiple spatial scales, while maintaining the original high-resolution features to preserve precise spatial details.
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao
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Learning Enriched Features for Fast Image Restoration and Enhancement
Transformers in Medical Imaging: A Survey
Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat, Fahad Shahbaz Khan, Huazhu Fu
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Learning Digital Camera Pipeline for Extreme Low-Light Imaging
Syed Waqas Zamir, Aditya Arora, Salman Khan, Fahad Shahbaz Khan, Ling Shao
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Low Light Image Enhancement via Global and Local Context Modeling
Aditya Arora, Muhammad Haris, Syed Waqas Zamir, Munawar Hayat, Fahad Shahbaz Khan, Ling Shao, Ming-Hsuan Yang
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Transformers in Vision: A Survey
ACM CSUR 2021
This survey provides a comprehensive overview of the Transformer models in the computer vision discipline, comparing advantages and limitations of popular techniques both in terms of architectural design and their experimental value. Finally, we provide an analysis on open research directions and possible future works.
Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, Mubarak Shah
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Filling the gaps in atrous convolution: semantic segmentation with a better context
Liyuan Liu, Yanwei Pang, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan, Ling Shao
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Vision Models for Wide Color Gamut Imaging in Cinema
Syed Waqas Zamir, Javier Vazquez-Corral, Marcelo Bertalmı́o
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Image processing applications through a variational perceptually-based color correction related to Retinex
Javier Vazquez-Corral, Syed Waqas Zamir, Adrian Galdran, David Pardo, Marcelo Bertalmı́o
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Gamut Mapping in Cinematography through Perceptually-based Contrast Modification
Syed Waqas Zamir, Javier Vazquez-Corral, Marcelo Bertalmı́o
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