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09/18/2023
Active anomaly detection based on deep one-class classification
Active learning has been utilized as an efficient tool in building anoma...
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09/18/2023
An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination
Most deep anomaly detection models are based on learning normality from ...
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02/13/2023
Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics
One-class classification has been a prevailing method in building deep a...
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10/28/2021
Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination
In this paper, we propose Normality-Calibrated Autoencoder (NCAE), which...
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09/14/2021
Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification
Recently, vehicle re-identification methods based on deep learning const...
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06/16/2021
Unsupervised Person Re-identification via Multi-Label Prediction and Classification based on Graph-Structural Insight
This paper addresses unsupervised person re-identification (Re-ID) using...
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03/03/2021
Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary
The key challenge of unsupervised vehicle re-identification (Re-ID) is l...
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04/03/2020
Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles
Traffic scene recognition, which requires various visual classification ...
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03/17/2020
Predictively Encoded Graph Convolutional Network for Noise-Robust Skeleton-based Action Recognition
In skeleton-based action recognition, graph convolutional networks (GCNs...
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01/30/2020
Unsupervised Pixel-level Road Defect Detection via Adversarial Image-to-Frequency Transform
In the past few years, the performance of road defect detection has been...
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10/22/2019
Drivers Drowsiness Detection using Condition-Adaptive Representation Learning Framework
We propose a condition-adaptive representation learning framework for th...
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10/21/2019
Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning
This paper addresses a boosting method for mapping functionality of neur...
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10/20/2019
