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04/11/2022
Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation
Recovering multi-person 3D poses from a single RGB image is a severely i...
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03/21/2022
Efficient Remote Photoplethysmography with Temporal Derivative Modules and Time-Shift Invariant Loss
We present a lightweight neural model for remote heart rate estimation f...
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03/18/2022
Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification
A critical limitation of current methods based on Neural Radiance Fields...
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11/02/2021
Body Size and Depth Disambiguation in Multi-Person Reconstruction from Single Images
We address the problem of multi-person 3D body pose and shape estimation...
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09/05/2021
Stochastic Neural Radiance Fields:Quantifying Uncertainty in Implicit 3D Representations
Neural Radiance Fields (NeRF) has become a popular framework for learnin...
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01/17/2021
Generating Attribution Maps with Disentangled Masked Backpropagation
Attribution map visualization has arisen as one of the most effective te...
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03/03/2020
Distilled Hierarchical Neural Ensembles with Adaptive Inference Cost
Deep neural networks form the basis of state-of-the-art models across a ...
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08/19/2019
Adaptative Inference Cost With Convolutional Neural Mixture Models
Despite the outstanding performance of convolutional neural networks (CN...
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01/24/2019
Learning Disentangled Representations with Reference-Based Variational Autoencoders
Learning disentangled representations from visual data, where different ...
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03/01/2018
Multi-Instance Dynamic Ordinal Random Fields for Weakly-supervised Facial Behavior Analysis
We propose a Multi-Instance-Learning (MIL) approach for weakly-supervise...
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09/06/2016
