相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization
Qi Wang et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)
Detecting Coherent Groups in Crowd Scenes by Multiview Clustering
Qi Wang et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)
SCLNet: Spatial context learning network for congested crowd counting
Shunzhou Wang et al.
NEUROCOMPUTING (2020)
Learning Multi-Level Density Maps for Crowd Counting
Xiaoheng Jiang et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2020)
Relational Attention Network for Crowd Counting
Anran Zhang et al.
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019) (2019)
ADCrowdNet: An Attention-Injective Deformable Convolutional Network for Crowd Understanding
Ning Liu et al.
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)
Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging
Jongpil Lee et al.
IEEE SIGNAL PROCESSING LETTERS (2017)
Spatiotemporal Modeling for Crowd Counting in Videos
Feng Xiong et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)
Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detectionn
Pingping Zhang et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)
Feature Mining for Localised Crowd Counting
Ke Chen et al.
PROCEEDINGS OF THE BRITISH MACHINE VISION CONFERENCE 2012 (2012)
Hough Forests for Object Detection, Tracking, and Action Recognition
Juergen Gall et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2011)
Segmentation and tracking of multiple humans in crowded environments
Tao Zhao et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2008)
Detecting pedestrians using patterns of motion and appearance
P Viola et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2005)
Robust real-time face detection
P Viola et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2004)
分享论文
