We propose an incremental improvement to Fully Convolutional Data Descri...
Equivariance of neural networks to transformations helps to improve thei...
In neural networks, the property of being equivariant to transformations...
The Gaussian kernel and its derivatives have already been employed for
C...
This paper analyses both nonlinear activation functions and spatial
max-...
Near out-of-distribution detection (OOD) aims at discriminating semantic...
Paris-CARLA-3D is a dataset of several dense colored point clouds of out...
This paper presents the computational challenge on differential geometry...
Point cloud datasets for perception tasks in the context of autonomous
d...
A fully convolutional neural network has a receptive field of limited si...
This paper addresses the issue of building a part-based representation o...
Following recent advances in morphological neural networks, we propose t...
Image segmentation is the process of partitioning an image into a set of...
Image segmentation is the process of partitioning an image into a set of...
The segmentation, seen as the association of a partition with an image, ...