activity
20192021
most citedUnimodal-uniform Constrained Wasserstein Training for Medical Diagnosis

4 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2021★ 1 cited

Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

Xiaofeng Liu, Bo Hu, Linghao Jin +6

In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training…

cs.CV2021★ 2 cited

Identity-aware Facial Expression Recognition in Compressed Video

Xiaofeng Liu, Linghao Jin, Xu Han +3

This paper targets to explore the inter-subject variations eliminated facial expression representation in the compressed video domain. Most of the previous methods process the RGB…

cs.CV2020★ 1 cited

Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training

Xiaofeng Liu, Yuzhuo Han, Song Bai +6

Semantic segmentation (SS) is an important perception manner for self-driving cars and robotics, which classifies each pixel into a pre-determined class. The widely-used cross entr…

cs.CV2020★ 1 cited

Mutual Information Regularized Identity-aware Facial ExpressionRecognition in Compressed Video

Xiaofeng Liu, Linghao Jin, Xu Han +1

How to extract effective expression representations that invariant to the identity-specific attributes is a long-lasting problem for facial expression recognition (FER). Most of th…

eess.IV2019★ 4 cited

Unimodal-uniform Constrained Wasserstein Training for Medical Diagnosis

Xiaofeng Liu, Xu Han, Yukai Qiao +2

The labels in medical diagnosis task are usually discrete and successively distributed. For example, the Diabetic Retinopathy Diagnosis (DR) involves five health risk levels: no DR…