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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 …
Crowdclip: Unsupervised crowd counting via vision-language model
Supervised crowd counting relies heavily on costly manual labeling, which is difficult and
expensive, especially in dense scenes. To alleviate the problem, we propose a novel …
expensive, especially in dense scenes. To alleviate the problem, we propose a novel …
Rethinking spatial invariance of convolutional networks for object counting
Previous work generally believes that improving the spatial invariance of convolutional
networks is the key to object counting. However, after verifying several mainstream counting …
networks is the key to object counting. However, after verifying several mainstream counting …
Steerer: Resolving scale variations for counting and localization via selective inheritance learning
Scale variation is a deep-rooted problem in object counting, which has not been effectively
addressed by existing scale-aware algorithms. An important factor is that they typically …
addressed by existing scale-aware algorithms. An important factor is that they typically …
Represent, compare, and learn: A similarity-aware framework for class-agnostic counting
Class-agnostic counting (CAC) aims to count all instances in a query image given few
exemplars. A standard pipeline is to extract visual features from exemplars and match them …
exemplars. A standard pipeline is to extract visual features from exemplars and match them …
Deep learning in crowd counting: A survey
Counting high‐density objects quickly and accurately is a popular area of research. Crowd
counting has significant social and economic value and is a major focus in artificial …
counting has significant social and economic value and is a major focus in artificial …
Indiscernible object counting in underwater scenes
Recently, indiscernible scene understanding has attracted a lot of attention in the vision
community. We further advance the frontier of this field by systematically studying a new …
community. We further advance the frontier of this field by systematically studying a new …
[PDF][PDF] Boosting crowd counting with transformers
Significant progress on the crowd counting problem has been achieved by integrating larger
context into convolutional neural networks (CNNs). This indicates that global scene context …
context into convolutional neural networks (CNNs). This indicates that global scene context …
Dynamic mixture of counter network for location-agnostic crowd counting
Crowd counting has attracted increasing attentions in recent years due to its challenges and
wide societal applications. Despite persevering efforts made by the research community …
wide societal applications. Despite persevering efforts made by the research community …
LCDnet: a lightweight crowd density estimation model for real-time video surveillance
Automatic crowd counting using density estimation has gained significant attention in
computer vision research. As a result, a large number of crowd counting and density …
computer vision research. As a result, a large number of crowd counting and density …