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04/04/2023
Learning to Name Classes for Vision and Language Models
Large scale vision and language models can achieve impressive zero-shot ...
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11/09/2022
Content-Diverse Comparisons improve IQA
Image quality assessment (IQA) forms a natural and often straightforward...
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10/07/2022
CLAD: A realistic Continual Learning benchmark for Autonomous Driving
In this paper we describe the design and the ideas motivating a new Cont...
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04/04/2022
Re-examining Distillation For Continual Object Detection
Training models continually to detect and classify objects, from new cla...
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12/13/2021
Long-tail Recognition via Compositional Knowledge Transfer
In this work, we introduce a novel strategy for long-tail recognition th...
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06/11/2021
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction
The impressive performance of deep convolutional neural networks in sing...
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10/05/2020
Probabilistic 3D surface reconstruction from sparse MRI information
Surface reconstruction from magnetic resonance (MR) imaging data is indi...
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08/21/2020
Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection
Object detection has witnessed significant progress by relying on large,...
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04/14/2020
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
The impressive performance of deep convolutional neural networks in sing...
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03/31/2020
DeepLPF: Deep Local Parametric Filters for Image Enhancement
Digital artists often improve the aesthetic quality of digital photograp...
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03/30/2020
Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem
This work investigates the task of unsupervised model personalization, a...
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02/28/2020
A Multi-Hypothesis Classification Approach to Color Constancy
Contemporary approaches frame the color constancy problem as learning ca...
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02/28/2020
A Multi-Hypothesis Approach to Color Constancy
Contemporary approaches frame the color constancy problem as learning ca...
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02/18/2020
EHSOD: CAM-Guided End-to-end Hybrid-Supervised Object Detection with Cascade Refinement
Object detectors trained on fully-annotated data currently yield state o...
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09/18/2019
Continual learning: A comparative study on how to defy forgetting in classification tasks
Artificial neural networks thrive in solving the classification problem ...
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11/28/2018
Meta-Learning for Few-shot Camera-Adaptive Color Constancy
Digital camera pipelines employ color constancy methods to estimate an u...
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07/30/2018
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors
Surface reconstruction is a vital tool in a wide range of areas of medic...
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06/19/2018
Learning Conditioned Graph Structures for Interpretable Visual Question Answering
Visual Question answering is a challenging problem requiring a combinati...
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06/05/2018
Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease
Graphs are widely used as a natural framework that captures interactions...
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03/29/2017
Exploring Heritability of Functional Brain Networks with Inexact Graph Matching
Data-driven brain parcellations aim to provide a more accurate represent...
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03/08/2017
Spectral Graph Convolutions for Population-based Disease Prediction
Exploiting the wealth of imaging and non-imaging information for disease...
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03/07/2017
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks
Evaluating similarity between graphs is of major importance in several c...
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11/15/2016
Comparison of Brain Networks with Unknown Correspondences
Graph theory has drawn a lot of attention in the field of Neuroscience d...
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11/10/2016
