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09/11/2023
MultIOD: Rehearsal-free Multihead Incremental Object Detector
Class-Incremental learning (CIL) is the ability of artificial agents to ...
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08/15/2023
Gradient-Based Post-Training Quantization: Challenging the Status Quo
Quantization has become a crucial step for the efficient deployment of d...
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08/10/2023
NUPES : Non-Uniform Post-Training Quantization via Power Exponent Search
Deep neural network (DNN) deployment has been confined to larger hardwar...
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08/09/2023
SAfER: Layer-Level Sensitivity Assessment for Efficient and Robust Neural Network Inference
Deep neural networks (DNNs) demonstrate outstanding performance across m...
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06/30/2023
Designing strong baselines for ternary neural network quantization through support and mass equalization
Deep neural networks (DNNs) offer the highest performance in a wide rang...
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03/21/2023
Fighting over-fitting with quantization for learning deep neural networks on noisy labels
The rising performance of deep neural networks is often empirically attr...
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03/06/2023
Fighting noise and imbalance in Action Unit detection problems
Action Unit (AU) detection aims at automatically caracterizing facial ex...
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01/24/2023
PowerQuant: Automorphism Search for Non-Uniform Quantization
Deep neural networks (DNNs) are nowadays ubiquitous in many domains such...
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08/06/2022
Multi-Task Transformer with uncertainty modelling for Face Based Affective Computing
Face based affective computing consists in detecting emotions from face ...
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07/08/2022
SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance
The leap in performance in state-of-the-art computer vision methods is a...
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03/28/2022
To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding
Batch-Normalization (BN) layers have become fundamental components in th...
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03/28/2022
REx: Data-Free Residual Quantization Error Expansion
Deep neural networks (DNNs) are nowadays ubiquitous in the computer visi...
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03/28/2022
SPIQ: Data-Free Per-Channel Static Input Quantization
Computationally expensive neural networks are ubiquitous in computer vis...
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03/24/2022
Privileged Attribution Constrained Deep Networks for Facial Expression Recognition
Facial Expression Recognition (FER) is crucial in many research domains ...
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03/23/2022
Multi-label Transformer for Action Unit Detection
Action Unit (AU) Detection is the branch of affective computing that aim...
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02/01/2022
Multi-Order Networks for Action Unit Detection
Deep multi-task methods, where several tasks are learned within a single...
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09/30/2021
RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging
Pruning Deep Neural Networks (DNNs) is a prominent field of study in the...
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05/31/2021
RED : Looking for Redundancies for Data-Free Structured Compression of Deep Neural Networks
Deep Neural Networks (DNNs) are ubiquitous in today's computer vision la...
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10/15/2020
THIN: THrowable Information Networks and Application for Facial Expression Recognition In The Wild
For a number of tasks solved using deep learning techniques, an exogenou...
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04/15/2020
DeeSCo: Deep heterogeneous ensemble with Stochastic Combinatory loss for gaze estimation
From medical research to gaming applications, gaze estimation is becomin...
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04/14/2020
Deep Entwined Learning Head Pose and Face Alignment Inside an Attentional Cascade with Doubly-Conditional fusion
Head pose estimation and face alignment constitute a backbone preprocess...
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10/21/2019
Tree-gated Deep Mixture-of-Experts For Pose-robust Face Alignment
Face alignment consists of aligning a shape model on a face image. It is...
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07/07/2019
Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild
Face alignment consists in aligning a shape model on a face in an image....
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04/04/2019
DeCaFA: Deep Convolutional Cascade for Face Alignment In The Wild
Face Alignment is an active computer vision domain, that consists in loc...
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03/05/2017
