Defocus Estimation
3 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Defocus Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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CUHK03
Motion Blurred and Defocused Dataset
Latest papers
Single image deep defocus estimation and its applications
Depth information is useful in many image processing applications.
Deep Defocus Map Estimation Using Domain Adaptation
codeslake/DMENet
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CVPR 2019
Our method is evaluated on publicly available blur detection and blur estimation datasets and the results show the state-of-the-art performance. In this paper, we propose the first end-to-end convolutional neural network (CNN) architecture, Defocus Map Estimation Network (DMENet), for spatially varying defocus map estimation.
A Unified Approach of Multi-scale Deep and Hand-crafted Features for Defocus Estimation
In this paper, we introduce robust and synergetic hand-crafted features and a simple but efficient deep feature from a convolutional neural network (CNN) architecture for defocus estimation.
