Search Results for author: Chengwei Chen

Found 6 papers, 0 papers with code

Novelty Detection via Contrastive Learning with Negative Data Augmentation

no code implementations18 Jun 2021 Chengwei Chen, Yuan Xie, Shaohui Lin, Ruizhi Qiao, Jian Zhou, Xin Tan, Yi Zhang, Lizhuang Ma

Moreover, our model is more stable for training in a non-adversarial manner, compared to other adversarial based novelty detection methods.

Contrastive Learning Data Augmentation +2

Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network

no code implementations9 Jul 2020 Nan Wang, Chengwei Chen, Yuan Xie, Lizhuang Ma

The brain structure in the collected data is complicated, thence, doctors are required to spend plentiful energy when diagnosing brain abnormalities.

Anomaly Detection Semi-supervised Anomaly Detection

Spoof Face Detection Via Semi-Supervised Adversarial Training

no code implementations22 May 2020 Chengwei Chen, Wang Yuan, Xuequan Lu, Lizhuang Ma

To capture the underlying structure of live faces data in latent representation space, we propose to train the live face data only, with a convolutional Encoder-Decoder network acting as a Generator.

Face Detection Face Recognition +1

Anomaly Detection by One Class Latent Regularized Networks

no code implementations5 Feb 2020 Chengwei Chen, Pan Chen, Haichuan Song, Yiqing Tao, Yuan Xie, Shouhong Ding, Lizhuang Ma

Anomaly detection is a fundamental problem in computer vision area with many real-world applications.

Anomaly Detection

Novelty Detection via Non-Adversarial Generative Network

no code implementations3 Feb 2020 Chengwei Chen, Wang Yuan, Yuan Xie, Yanyun Qu, Yiqing Tao, Haichuan Song, Lizhuang Ma

One-class novelty detection is the process of determining if a query example differs from the training examples (the target class).

Image Reconstruction

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