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07/05/2021
MixStyle Neural Networks for Domain Generalization and Adaptation
Convolutional neural networks (CNNs) often have poor generalization perf...
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06/18/2021
Residual Contrastive Learning for Joint Demosaicking and Denoising
The breakthrough of contrastive learning (CL) has fueled the recent succ...
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06/17/2021
Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error
Calibration of neural networks is a topical problem that is becoming inc...
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03/22/2021
Context-Aware Layout to Image Generation with Enhanced Object Appearance
A layout to image (L2I) generation model aims to generate a complicated ...
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03/16/2020
Domain Adaptive Ensemble Learning
The problem of generalizing deep neural networks from multiple source do...
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10/15/2019
Learning Generalisable Omni-Scale Representations for Person Re-Identification
An effective person re-identification (re-ID) model should learn feature...
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01/31/2019
Feature-Critic Networks for Heterogeneous Domain Generalization
The well known domain shift issue causes model performance to degrade wh...
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04/13/2018
Learning Deep Sketch Abstraction
Human free-hand sketches have been studied in various contexts including...
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03/21/2016
