CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共5条,第1-5条 帮助

限定条件                    
已选(0)清除 条数/页:   排序方式:
A Recurrent Attention and Interaction Model for Pedestrian Trajectory Prediction 期刊论文
Journal of Automatica Sinica, 2020, 期号: *, 页码: *
作者:  Li Xuesong;  Liu Yating;  Wang Kunfeng;  Wang Fei-Yue
Adobe PDF(5533Kb)  |  收藏  |  浏览/下载:172/49  |  提交时间:2020/06/08
Trajectory prediction  recurrent attention and interaction model  Long Short-Term Memory  deep learning  
Mask SSD: An Effective Single-Stage Approach to Object Instance Segmentation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 1, 页码: 2078-2093
作者:  Zhang, Hui;  Tian, Yonglin;  Wang, Kunfeng;  Zhang, Wensheng;  Wang, Fei-Yue
Adobe PDF(4983Kb)  |  收藏  |  浏览/下载:370/163  |  提交时间:2020/03/30
Object detection  instance segmentation  feedback features  single-shot detector  
MFR-CNN: Incorporating Multi-Scale Features and Global Information for Traffic Object Detection 期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 卷号: 67, 期号: 9, 页码: 8019-8030
作者:  Zhang, Hui;  Wang, Kunfeng;  Tian, Yonglin;  Gou, Chao;  Wang, Fei-Yue
Adobe PDF(4636Kb)  |  收藏  |  浏览/下载:316/63  |  提交时间:2019/12/16
Traffic Object Detection  Convolutional Neural Network  Multi-scale Features  Global Information  
Generative Adversarial Networks: Introduction and Outlook 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2017, 卷号: 4, 期号: 4, 页码: 588-598
作者:  Kunfeng Wang;  Chao Gou;  Yanjie Duan;  Yilun Lin;  Xinhu Zheng;  Fei-Yue Wang
浏览  |  Adobe PDF(16945Kb)  |  收藏  |  浏览/下载:372/42  |  提交时间:2018/01/08
Acp Approach  Adversarial Learning  Generative Adversarial Networks (Gans)  Generative Models  Parallel Intelligence  Zero-sum Game  
A Multi-view Learning Approach to Foreground Detection for Traffic Surveillance Applications 期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 卷号: 65, 期号: 6, 页码: 4144-4158
作者:  Wang, Kunfeng;  Liu, Yuqiang;  Gou, Chao;  Wang, Fei-Yue;  Wang, Kunfeng(王坤峰)
浏览  |  Adobe PDF(1153Kb)  |  收藏  |  浏览/下载:441/123  |  提交时间:2016/04/06
Conditional Independence  Foreground Detection  Heterogeneous Features  Markov Random Field (Mrf)  Multi-view Learning