Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …

We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic
segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

We present a novel framework to generate and rank plausible hypotheses for the spatial
extent of objects in images using bottom-up computational processes and mid-level …

Object recognition systems constitute a deeply entrenched and omnipresent component of
modern intelligent systems. Research on object recognition algorithms has led to advances …

We present a novel framework for generating and ranking plausible objects hypotheses in
an image using bottom-up processes and mid-level cues. The object hypotheses are …

We present RigNet, an end-to-end automated method for producing animation rigs from
input character models. Given an input 3D model representing an articulated character …

Structural magnetic resonance imaging data are frequently analysed to reveal
morphological changes of the human brain in dementia. Most contemporary imaging …

This paper introduces and evaluates a novel way of processing human activities based on
unique combinations of interpretable categorical high-level features with applications to …