[Project] [Paper] [Code] [Online Demo] [API] [Related Work: GP-GAN (for Image Blending)]
source | step 1 | step 2 | step 3 | step 4 | step 5 | output |
---|---|---|---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
A2-RL (aka. Aesthetics Aware Reinforcement Learning) is the author's implementation of the RL-based automatic image cropping algorithm described in:
A2-RL: Aesthetics Aware Reinforcement Learning for Automatic Image Cropping
Debang Li, Huikai Wu, Junge Zhang, Kaiqi Huang
Given a source image, our algorithm could take actions step by step to find almost the best cropping window on source image.
Contact: Debang Li ([email protected])
Results compared with baseline methods (more results)
Source | VFN+Sliding window | A2-RL | Ground Truth |
---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
@article{li2017a2,
title={A2-RL: Aesthetics Aware Reinforcement Learning for Automatic Image Cropping},
author={Li, Debang and Wu, Huikai and Zhang, Junge and Huang, Kaiqi},
journal={arXiv preprint arXiv:1709.04595},
year={2017}
}