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Multi-Stage Contextual Deep Learning for Pedestrian Detection
  • 所属机构名称：中国科学院深圳先进技术研究院
  • 会议名称：14th IEEE International Conference on Computer Vision, ICCV 2013
  • 时间：2013.12.12
  • 成果类型：会议
  • 相关项目：用于交通管理的新一代智能视频监控系统的研究与开发
作者： Xingyu Zeng|Wanli Ouyang|Xiaogang Wang|
同会议论文项目
用于交通管理的新一代智能视频监控系统的研究与开发
期刊论文 1 会议论文 20
同项目会议论文
Graph Degree Linkage: Agglomerative Clustering on a Directed Graph
Random Field Topic Model for Semantic Region Analysis in Crowded Scenes from Tracklets
Understanding Collective Crowd Behaviors: Learning a Mixture Model of Dynamic Pedestrian-Agents
Transferring a Generic Pedestrian Detector Towards Specific Scenes
A discriminative deep model for pedestrian detection with occlusion handling
Hybrid Deep Learning for Face Verification
Joint Deep Learning for Pedestrian Detection
Person Re-identification by Salience Matching
Human Reidentification with Transferred Metric Learning
Graph Degree Linkage: Agglomerative Clustering on a Directed Graph
Measuring Crowd Collectiveness
Modeling Mutual Visibility Relationship with a Deep Model in Pedestrian Detection
Unsupervised Salience Learning for Person Re-identification
Locally Aligned Feature Transforms across Views
Coherent Filtering: Detecting Coherent Motions from Crowd Clutters
Single-Pedestrian Detection aided by Multi-pedestrian Detection
Hierarchical face parsing via deep learning
Optical Flow Estimation Using Learned Sparse Model
Deep Convolutional Network Cascade for Facial Point Detection