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Found 4 papers, 4 papers with code
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
For training, only one set of source input images is therefore provided in the challenge.
Frequency Separation for Real-World Super-Resolution
Furthermore, we propose to separate the low and high image frequencies and treat them differently during training.
Efficient Smoothing of Dilated Convolutions for Image Segmentation
Dilated Convolutions have been shown to be highly useful for the task of image segmentation.
Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning
Learning in sparse reward settings remains a challenge in Reinforcement Learning, which is often addressed by using intrinsic rewards.
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