activity
20182022
most citedRegularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting

68 citations · 86 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV20221 cited

CNTN: Cyclic Noise-tolerant Network for Gait Recognition

Weichen Yu, Hongyuan Yu, Yan Huang +2

Gait recognition aims to identify individuals by recognizing their walking patterns. However, an observation is made that most of the previous gait recognition methods degenerate s…

cs.CV202216 cited

Generalized Inter-class Loss for Gait Recognition

Weichen Yu, Hongyuan Yu, Yan Huang +1

Gait recognition is a unique biometric technique that can be performed at a long distance non-cooperatively and has broad applications in public safety and intelligent traffic syst…

cs.LG202268 cited

Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting

Hongyuan Yu, Ting Li, Weichen Yu +4

Multivariate time-series forecasting is a critical task for many applications, and graph time-series network is widely studied due to its capability to capture the spatial-temporal…

eess.IV2022

Consecutive Knowledge Meta-Adaptation Learning for Unsupervised Medical Diagnosis

Yumin Zhang, Yawen Hou, Xiuyi Chen +2

Deep learning-based Computer-Aided Diagnosis (CAD) has attracted appealing attention in academic researches and clinical applications. Nevertheless, the Convolutional Neural Networ…

cs.CV2020

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

Houwen Peng, Hao Du, Hongyuan Yu +3

One-shot weight sharing methods have recently drawn great attention in neural architecture search due to high efficiency and competitive performance. However, weight sharing across…

cs.CV20201 cited

Recurrent Deconvolutional Generative Adversarial Networks with Application to Text Guided Video Generation

Hongyuan Yu, Yan Huang, Lihong Pi +1

This paper proposes a novel model for video generation and especially makes the attempt to deal with the problem of video generation from text descriptions, i.e., synthesizing real…