Aesthetic-Driven Image Enhancement by Adversarial Learning

17 Jul 2017Yubin DengChen Change LoyXiaoou Tang

We introduce EnhanceGAN, an adversarial learning based model that performs automatic image enhancement. Traditional image enhancement frameworks typically involve training models in a fully-supervised manner, which require expensive annotations in the form of aligned image pairs... (read more)

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Evaluation Results from the Paper


 SOTA for Image Cropping on AVA (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
COMPARE
Image Cropping AVA Crop Bounding Box AP 1 # 1