Feb 19, 2024 · In this paper, we address the challenging problem of crowd counting in congested scenes. Specifically, we present Inverse Attention Guided ...
[SGANet] Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss (TITS) [paper]; [CTASNet] Counting Varying Density Crowds Through ...
This work uses deep convolutional neural networks to estimate the crowd count by combining a suitable loss function and distribution matching and proposes ...
Oct 7, 2022 · Survey paper. A survey on deep learning-based single image crowd counting: Network design, loss function and supervisory signal.
Nov 18, 2019 · Crowd counting is one of the keys to automatic crowd behaviour analysis. Crowd counting using deep convolutional neural networks (CNN) has ...
Missing: Joint SASNet Batch Normalization
(PDF) A Crowd Counting Framework Combining with Crowd Location
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Jan 5, 2024 · In this paper, a new framework is proposed to resolve the problem. The proposed framework includes two parts. The first part is a fully ...
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Aptoula, Crowd counting via joint SASNet and a guided batch normalization network, 31. IEEE Signal Processing and Communication Applications Conference ...
Crowd counting via joint SASNet and a guided batch normalization network. C Haldız, SF Ismael, H Çelebi, E Aptoula. 2023 31st Signal Processing and ...
and Çelebi, Hasari and Aptoula, Erchan, "Crowd counting via joint SASNet and a guided batch normalization network", 31st Signal Processing and ...
Crowd Counting via Joint SASNet and a Guided Batch Normalization Network. ... using One-shot Image-to-Image Translation via Latent Representation Mixing. CoRR ...