34 citations · 213 across the 28 of their papers we have counts for
8 papers · 1 filter
Towards Disentangled Representations for Human Retargeting by Multi-view Learning
Chao Yang, Xiaofeng Liu, Qingming Tang +1
We study the problem of learning disentangled representations for data across multiple domains and its applications in human retargeting. Our goal is to map an input image to an id…
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…
Conservative Wasserstein Training for Pose Estimation
Xiaofeng Liu, Yang Zou, Tong Che +4
This paper targets the task with discrete and periodic class labels ( pose/orientation estimation) in the context of deep learning. The commonly used cross-entropy or regres…
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
Tong Che, Xiaofeng Liu, Site Li +4
AI Safety is a major concern in many deep learning applications such as autonomous driving. Given a trained deep learning model, an important natural problem is how to reliably ver…
Attention Control with Metric Learning Alignment for Image Set-based Recognition
Xiaofeng Liu, Zhenhua Guo, Jane You +1
This paper considers the problem of image set-based face verification and identification. Unlike traditional single sample (an image or a video) setting, this situation assumes the…
Permutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition
Xiaofeng Liu, Zhenhua Guo, Site Li +4
We consider the problem of comparing the similarity of image sets with variable-quantity, quality and un-ordered heterogeneous images. We use feature restructuring to exploit the c…