Results 61 to 70 of about 322,190 (190)
Statistical t+2D subband modelling for crowd counting [PDF]
, 2018 Counting people automatically in a crowded scenario is important to assess safety and to determine behaviour in surveillance operations. In this paper we propose a new algorithm using the statistics of the spatio-temporal wavelet subbands. A t+2D lifting
Deepayan Bhowmik +3 more
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BUILDING A NEW CROWD-COUNTING ARCHITECTURE
, 2023 Crowd counting has become necessary in the age of information technology and network development; with many different goals, people have needed more services to meet their work.
Hung Nguyen Viet (14281193) +1 more
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Curriculum for Crowd Counting: Is It Worthy?
Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and ApplicationsAccepted version of the paper in 19th International Conference on Computer Vision Theory and Applications (VISAPP), Rome, Italy, 27-19 February ...
Muhammad Asif Khan 0001 +2 more
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Weighing Counts: Sequential Crowd Counting by Reinforcement Learning [PDF]
, 2020 We formulate counting as a sequential decision problem and present a novel crowd counting model solvable by deep reinforcement learning. In contrast to existing counting models that directly output count values, we divide one-step estimation into a sequence of much easier and more tractable sub-decision problems.
Liang Liu 0001 +5 more
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ST-CNN: Spatial-Temporal Convolutional Neural Network for crowd counting in videos
, 2019 The task of crowd counting and density maps estimating from videos is challenging due to severe occlusions, scene perspective distortions and diverse crowd distributions.
Gao, Y, Han, J, Zhang, B, Miao, Y
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Crowd counting with sparse annotation
Pattern RecognitionThis paper presents a new annotation method called Sparse Annotation (SA) for crowd counting, which reduces human labeling efforts by sparsely labeling individuals in an image. We argue that sparse labeling can reduce the redundancy of full annotation and capture more diverse information from distant individuals that is not fully captured by Partial ...
Shiwei Zhang +5 more
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Learning Multi-Level Features to Improve Crowd Counting
IEEE Access, 2020 Crowd counting is a task that aims to estimate the number of people in an image. Recent crowd counting methods make significant progress by employing convolutional neural networks to regress crowd density maps.
Zhanqiang Huo +4 more
doaj +1 more source
Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss [PDF]
, 2022 Automatic crowd behaviour analysis is an important task for intelligent transportation systems to enable effective flow control and dynamic route planning for varying road participants.
Wang, Q., Breckon, T.P.
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Engineering ProceedingsIn recent years, with the rise of smart education, crowd counting technology has garnered increasing attention for its applications in educational environments.
Wenqian Jiang +3 more
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Remote Sensing, 2022 Recent advances in deep learning-based image processing have enabled significant improvements in multiple computer vision fields, with crowd counting being no exception. Crowd counting is still attracting research interest due to its potential usefulness
Bartosz Ptak +3 more
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