Large scale vision and language models can achieve impressive zero-shot
...
Image quality assessment (IQA) forms a natural and often straightforward...
In this paper we describe the design and the ideas motivating a new Cont...
Training models continually to detect and classify objects, from new cla...
In this work, we introduce a novel strategy for long-tail recognition th...
The impressive performance of deep convolutional neural networks in
sing...
Surface reconstruction from magnetic resonance (MR) imaging data is
indi...
Object detection has witnessed significant progress by relying on large,...
The impressive performance of deep convolutional neural networks in
sing...
Digital artists often improve the aesthetic quality of digital photograp...
This work investigates the task of unsupervised model personalization,
a...
Contemporary approaches frame the color constancy problem as learning ca...
Contemporary approaches frame the color constancy problem as learning ca...
Object detectors trained on fully-annotated data currently yield state o...
Artificial neural networks thrive in solving the classification problem ...
Digital camera pipelines employ color constancy methods to estimate an
u...
Surface reconstruction is a vital tool in a wide range of areas of medic...
Visual Question answering is a challenging problem requiring a combinati...
Graphs are widely used as a natural framework that captures interactions...
Data-driven brain parcellations aim to provide a more accurate represent...
Exploiting the wealth of imaging and non-imaging information for disease...
Evaluating similarity between graphs is of major importance in several
c...
Graph theory has drawn a lot of attention in the field of Neuroscience d...
Understanding brain connectivity in a network-theoretic context has show...