Cross-modal Unsupervised Domain Adaptation (UDA) aims to exploit the
com...
Existing methods for large-scale point cloud semantic segmentation requi...
Weakly supervised point cloud semantic segmentation methods that require...
Information Bottleneck (IB) based multi-view learning provides an inform...
Crowd Counting has important applications in public safety and pandemic
...
Convolutional neural networks (CNNs) are highly successful for
super-res...
Hidden features in neural network usually fail to learn informative
repr...
Single image dehazing is a challenging ill-posed problem due to the seve...
The Information Bottleneck (IB) provides an information theoretic princi...
Boundary information plays a significant role in 2D image segmentation, ...
This paper reviews the AIM 2020 challenge on efficient single image
supe...
This paper reviews the Challenge on Image Demoireing that was part of th...
Despite recent progress on semantic segmentation, there still exist huge...
One-class novelty detection is the process of determining if a query exa...
This paper reviews the first-ever image demoireing challenge that was pa...
Image quality measurement is a critical problem for image super-resoluti...
Exploring the information among multiple views usually leads to more
pro...
Most recently, tensor-SVD is implemented on multi-view self-representati...
We investigate the scalable image classification problem with a large nu...
In this paper, we address the multi-view subspace clustering problem. Ou...
It remains a challenge to simultaneously remove geometric distortion and...