We present an approach to accelerating a wide variety of image processing operators. Our approach uses a fully-convolutional network that is trained on input-output pairs that demonstrate the operator's action. After training, the original operator need not be run at all. The trained network oper...
Learning an Adaptive Model for Extreme Low-light Raw Image Processing Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio parameter must be chosen manually to complete the ...
pythonmachine-learninginformation-retrievaldata-miningocrdeep-learningimage-processingcnnpytorchlstmoptical-character-recognitioncrnnscene-textscene-text-recognitioneasyocr UpdatedSep 24, 2024 Python amusi/CVPR2025-Papers-with-Code Star19.8k CVPR 2025 论文和开源项目合集 ...
The resolution of cameras is increasing, and speedup of various image processing is required to accompany this increase. A simple way of acceleration is pr
Towards Effective Image Forensics via A Novel Computationally Efficient Framework and A New Image Splice Dataset ( Signal, Image and Video Processing (IF: 2.3, not included in CCFs), '24 ) [Paper]2023 GreatSplicing: A Semantically Rich Splicing Dataset (arXiv '23) [Paper] [Dataset] Multi-...
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computational photography and photo enhancements, so we refer the interested reader to various other standard resources in Digital Image Processing and Signal Processing as we go along [4, 9, 325, 326], and we also point out interesting research papers that will enhance understanding of the ...
For customization of the pipeline to specific tasks, all code is easily accessible and well documented. Conclusions With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline....
By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection. See our privacy policy for more information on the use of your perso...
In signal processing, sparse coding consists of representing data with linear combinations of a few dictionary elements. Subsequently, the corresponding tools have been widely adopted by several scientific communities such as neuroscience, bioinformatics, or computer vision. The goal of this monograph is...