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In this paper, we propose a fast fully convolutional neural network (FCNN) for crowd segmentation.
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Pedestrian detection in crowded scenes
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Simultaneous Estimation of Segmentation and Shape
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Detecting Pedestrians Using Patterns of Motion and Appearance
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A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis
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Fast Crowd Segmentation Using Shape Indexing
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Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
A. B. Chan and N. Vasconcelos · 2008
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Segmentation and Tracking of Multiple Humans in Crowded Environments
T. Zhao, R. Nevatia, and B. Wu · 2008
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Learning to associate: HybridBoosted multi-target tracker for crowded scene
Y. Li, C. Huang, and R. Nevatia · 2009
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Counting people with low-level features and Bayesian regression
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Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
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Imagenet classification with deep convolutional neural networks
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Crossing the Line: Crowd Counting by Integer Programming with Local Features
Z. Ma and A. B. Chan · 2013
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OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. A. LeCun · 2013
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Multi-stage Contextual Deep Learning for Pedestrian Detection
X. Zeng, W. Ouyang, and X. Wang · 2013
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Measuring crowd collectiveness
B. Zhou, X. Tang, and X. Wang · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Large-scale Video Classification with Convolutional Neural Networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and F.-F. Li · 2014
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Identifying behaviors in crowd scenes using stability analysis for dynamical systems
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Coherent Filtering: Detecting Coherent Motions from Crowd Clutters
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Structured Forests for Fast Edge Detection
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Learning Hierarchical Features for Scene Labeling
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Multi-source Multi-scale Counting in Extremely Dense Crowd Images
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Network In Network
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Recurrent Convolutional Neural Networks for Scene Labeling
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CNN Features off-the-shelf: an Astounding Baseline for Recognition
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Scene-Independent Group Profiling in Crowd
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Going Deeper with Convolutions
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Profiling stationary crowd groups
S. Yi and X. Wang · 2014
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L0 Regularized Stationary Time Estimation for Crowd Group Analysis
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