Search Results for author: Jane You

Found 18 papers, 2 papers with code

Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model

no code implementations26 Aug 2022 Lingsheng Kong, Bo Hu, Xiongchang Liu, Jun Lu, Jane You, Xiaofeng Liu

Deep learning is usually data starved, and the unsupervised domain adaptation (UDA) is developed to introduce the knowledge in the labeled source domain to the unlabeled target domain.

Image Classification Pseudo Label +2

Adversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate

no code implementations ICCV 2021 Xiaofeng Liu, Zhenhua Guo, Site Li, Fangxu Xing, Jane You, C. -C. Jay Kuo, Georges El Fakhri, Jonghye Woo

In this work, we propose an adversarial unsupervised domain adaptation (UDA) approach with the inherent conditional and label shifts, in which we aim to align the distributions w. r. t.

Unsupervised Domain Adaptation

Energy-constrained Self-training for Unsupervised Domain Adaptation

no code implementations1 Jan 2021 Xiaofeng Liu, Bo Hu, Xiongchang Liu, Jun Lu, Jane You, Lingsheng Kong

Unsupervised domain adaptation (UDA) aims to transfer the knowledge on a labeled source domain distribution to perform well on an unlabeled target domain.

Image Classification Semantic Segmentation +1

Identity-aware Facial Expression Recognition in Compressed Video

no code implementations1 Jan 2021 Xiaofeng Liu, Linghao Jin, Xu Han, Jun Lu, Jane You, Lingsheng Kong

In the up to two orders of magnitude compressed domain, we can explicitly infer the expression from the residual frames and possible to extract identity factors from the I frame with a pre-trained face recognition network.

Face Recognition Facial Expression Recognition

Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

no code implementations1 Jan 2021 Xiaofeng Liu, Xiongchang Liu, Bo Hu, Wenxuan Ji, Fangxu Xing, Jun Lu, Jane You, C. -C. Jay Kuo, Georges El Fakhri, Jonghye Woo

Recent advances in unsupervised domain adaptation (UDA) show that transferable prototypical learning presents a powerful means for class conditional alignment, which encourages the closeness of cross-domain class centroids.

Medical Diagnosis Unsupervised Domain Adaptation

Mutual Information Regularized Identity-aware Facial ExpressionRecognition in Compressed Video

no code implementations20 Oct 2020 Xiaofeng Liu, Linghao Jin, Xu Han, Jane You

In the up to two orders of magnitude compressed domain, we can explicitly infer the expression from the residual frames and possibly extract identity factors from the I frame with a pre-trained face recognition network.

Face Recognition Facial Expression Recognition

Conservative Wasserstein Training for Pose Estimation

no code implementations ICCV 2019 Xiaofeng Liu, Yang Zou, Tong Che, Peng Ding, Ping Jia, Jane You, Kumar B. V. K

We propose to incorporate inter-class correlations in a Wasserstein training framework by pre-defining ($i. e.,$ using arc length of a circle) or adaptively learning the ground metric.

Pose Estimation

Attention Control with Metric Learning Alignment for Image Set-based Recognition

no code implementations5 Aug 2019 Xiaofeng Liu, Zhenhua Guo, Jane You, B. V. K. Vijaya Kumar

The importance of each image is usually considered either equal or based on a quality assessment of that image independent of other images and/or videos in that image set.

Face Recognition Face Verification +1

Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression

2 code implementations24 Jun 2019 Mu Li, Kede Ma, Jane You, David Zhang, WangMeng Zuo

For the former, we directly apply a CCN to the binarized representation of an image to compute the Bernoulli distribution of each code for entropy estimation.

Image Compression

Learning Content-Weighted Deep Image Compression

1 code implementation1 Apr 2019 Mu Li, WangMeng Zuo, Shuhang Gu, Jane You, David Zhang

Learning-based lossy image compression usually involves the joint optimization of rate-distortion performance.

Image Compression

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