Creating high quality and realistic materials in computer graphics is a
...
Generative Adversarial Networks (GANs) have demonstrated their ability t...
Polygonal meshes have become the standard for discretely approximating 3...
Humans can learn incrementally, whereas neural networks forget previousl...
Continual learning has recently attracted attention from the research
co...
Graph-structured scene descriptions can be efficiently used in generativ...
Video saliency prediction has recently attracted attention of the resear...
Generating images from semantic visual knowledge is a challenging task, ...
Early detection of precancerous cysts or neoplasms, i.e., Intraductal
Pa...
In the medical field, multi-center collaborations are often sought to yi...
In Continual Learning (CL), a neural network is trained on a stream of d...
This work investigates the entanglement between Continual Learning (CL) ...
We present MIDGARD, an open source simulation platform for autonomous ro...
We propose a novel 3D fully convolutional deep network for automated pan...
In this paper we present SurfaceNet, an approach for estimating
spatiall...
COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pande...
In this work, we propose a 3D fully convolutional architecture for video...
Being able to estimate the traversability of the area surrounding a mobi...
This paper tackles the problem of learning brain-visual representations ...
This paper presents an approach for top-down saliency detection guided b...
What if we could effectively read the mind and transfer human visual
cap...
Video object segmentation can be considered as one of the most challengi...