A review of vision-based traffic semantic understanding in ITSs
J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …
situations and emergencies more accurately and provide a more accurate basis for anomaly …
Revisiting crowd counting: State-of-the-art, trends, and future perspectives
Crowd counting is an effective tool for situational awareness in public places. Automated
crowd counting using images and videos is an interesting yet challenging problem that has …
crowd counting using images and videos is an interesting yet challenging problem that has …
Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method
We introduce a new large scale unconstrained crowd counting dataset (JHU-CROWD++)
that contains “4,372” images with “1.51 million” annotations. In comparison to existing …
that contains “4,372” images with “1.51 million” annotations. In comparison to existing …
Cross-modal collaborative representation learning and a large-scale rgbt benchmark for crowd counting
Crowd counting is a fundamental yet challenging task, which desires rich information to
generate pixel-wise crowd density maps. However, most previous methods only used the …
generate pixel-wise crowd density maps. However, most previous methods only used the …
A self-training approach for point-supervised object detection and counting in crowds
In this article, we propose a novel self-training approach named Crowd-SDNet that enables
a typical object detector trained only with point-level annotations (ie, objects are labeled with …
a typical object detector trained only with point-level annotations (ie, objects are labeled with …
WheatNet: A lightweight convolutional neural network for high-throughput image-based wheat head detection and counting
For a globally recognized plant breeding organization, manually recorded field observation
data is crucial for plant breeding decision making. However, certain phenotypic traits such …
data is crucial for plant breeding decision making. However, certain phenotypic traits such …
Locating and counting heads in crowds with a depth prior
To simultaneously estimate the number of heads and locate heads with bounding boxes, we
resort to detection-based crowd counting by leveraging RGB-D data and design a dual-path …
resort to detection-based crowd counting by leveraging RGB-D data and design a dual-path …
Learning to count in the crowd from limited labeled data
Recent crowd counting approaches have achieved excellent performance. However, they
are essentially based on fully supervised paradigm and require large number of annotated …
are essentially based on fully supervised paradigm and require large number of annotated …
Encoder-decoder based convolutional neural networks with multi-scale-aware modules for crowd counting
In this paper, we propose two modified neural networks based on dual path multi-scale
fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by …
fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by …
Harnessing perceptual adversarial patches for crowd counting
Crowd counting, which has been widely adopted for estimating the number of people in
safety-critical scenes, is shown to be vulnerable to adversarial examples in the physical …
safety-critical scenes, is shown to be vulnerable to adversarial examples in the physical …