Search Results for author:
Found 7 papers, 6 papers with code
CropMix: Sampling a Rich Input Distribution via Multi-Scale Cropping
We present a simple method, CropMix, for the purpose of producing a rich input distribution from the original dataset distribution.
GOSS: Towards Generalized Open-set Semantic Segmentation
In this paper, we present and study a new image segmentation task, called Generalized Open-set Semantic Segmentation (GOSS).
You Only Cut Once: Boosting Data Augmentation with a Single Cut
We present You Only Cut Once (YOCO) for performing data augmentations.
Blind Image Decomposition
We present and study a novel task named Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that is, both the source components involved in mixing as well as the mixing mechanism are unknown.
Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
There are 2000 reference restored images and 6003 original underwater images in the unpaired training set.
Dual Contrastive Learning for Unsupervised Image-to-Image Translation
Unsupervised image-to-image translation tasks aim to find a mapping between a source domain X and a target domain Y from unpaired training data.
Single Underwater Image Restoration by Contrastive Learning
Underwater image restoration attracts significant attention due to its importance in unveiling the underwater world.
