Comments (1)
From the paper:
Datasets.We utilize two sources of training data:
•The MIT-Adobe FiveK Dataset. Bychkovsky et al. [2011]compiled a photo dataset consisting of 5,000RAW images and retouched versions of each by five experts. In this work, we randomly separate the dataset into three parts: (part 1) 2,000input RAW images, (part 2) 2,000 retouched images by retoucher C, and (part 3) 1,000input RAW images for testing. The three parts have no intersection with each other.
from exposure.
Related Issues (20)
- how to train it in supervised version HOT 1
- Is there any chance to get this working in Win64? HOT 2
- RAW Camera file exports are very small
- How to convert other imgs through the parameters we get from one img inferring? HOT 1
- Question about value network
- SaturationPlus Filter Parameter returns 0 HOT 1
- How can I convert the input image from ProPhoto RGB color space to sRGB color space ?
- how to train on my own dataset? HOT 1
- Testing procedure gets stuck at "initializing..."
- 数据集无法下载 HOT 2
- How can I do reverse-engineer? HOT 1
- the parameters of each filter
- partI, partII 文件未知或者已损坏是什么情况啊?
- Training set setup
- Error while importing Util HOT 3
- The inference time is getting longer and longer
- About demosaicing
- Inquiry about the Possibility of Duplicate Retouching Operations in Reinforcement Learning Mode HOT 1
- exposure crashing
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from exposure.