activity
20142020
most citedJoint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference

40 citations · 94 across the 6 of their papers we have counts for

collaborators

6 papers

cs.PF20201 cited

AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite

Wanling Gao, Fei Tang, Jianfeng Zhan +31

Domain-specific software and hardware co-design is encouraging as it is much easier to achieve efficiency for fewer tasks. Agile domain-specific benchmarking speeds up the process…

cs.LG2019

Distributed Generative Adversarial Net

Xiaoyu Wang, Ye Deng, Jinjun Wang

Recently the Generative Adversarial Network has become a hot topic. Considering the application of GAN in multi-user environment, we propose Distributed-GAN. It enables multiple us…

cs.LG201940 cited

Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference

Xianfeng Tang, Boqing Gong, Yanwei Yu +4

Real-time traffic volume inference is key to an intelligent city. It is a challenging task because accurate traffic volumes on the roads can only be measured at certain locations w…

cs.CV201633 cited

A Recurrent Encoder-Decoder Network for Sequential Face Alignment

Xi Peng, Rogerio S. Feris, Xiaoyu Wang +1

We propose a novel recurrent encoder-decoder network model for real-time video-based face alignment. Our proposed model predicts 2D facial point maps regularized by a regression lo…

cs.CV20148 cited

Object-centric Sampling for Fine-grained Image Classification

Xiaoyu Wang, Tianbao Yang, Guobin Chen +1

This paper proposes to go beyond the state-of-the-art deep convolutional neural network (CNN) by incorporating the information from object detection, focusing on dealing with fine-…

cs.CV201412 cited

Generic Object Detection With Dense Neural Patterns and Regionlets

Will Y. Zou, Xiaoyu Wang, Miao Sun +1

This paper addresses the challenge of establishing a bridge between deep convolutional neural networks and conventional object detection frameworks for accurate and efficient gener…