Human action recognition from various data modalities: A review

Z Sun, Q Ke, H Rahmani, M Bennamoun… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Languagebind: Extending video-language pretraining to n-modality by language-based semantic alignment

B Zhu, B Lin, M Ning, Y Yan, J Cui, HF Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
The video-language (VL) pretraining has achieved remarkable improvement in multiple
downstream tasks. However, the current VL pretraining framework is hard to extend to …

Uav-human: A large benchmark for human behavior understanding with unmanned aerial vehicles

T Li, J Liu, W Zhang, Y Ni… - Proceedings of the …, 2021 - openaccess.thecvf.com
Human behavior understanding with unmanned aerial vehicles (UAVs) is of great
significance for a wide range of applications, which simultaneously brings an urgent …

Human movement datasets: An interdisciplinary scoping review

T Olugbade, M Bieńkiewicz, G Barbareschi… - ACM Computing …, 2022 - dl.acm.org
Movement dataset reviews exist but are limited in coverage, both in terms of size and
research discipline. While topic-specific reviews clearly have their merit, it is critical to have a …

[HTML][HTML] Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization

Y Himeur, S Al-Maadeed, H Kheddar… - … Applications of Artificial …, 2023 - Elsevier
Recently, developing automated video surveillance systems (VSSs) has become crucial to
ensure the security and safety of the population, especially during events involving large …

Semantics-aware adaptive knowledge distillation for sensor-to-vision action recognition

Y Liu, K Wang, G Li, L Lin - IEEE Transactions on Image …, 2021 - ieeexplore.ieee.org
Existing vision-based action recognition is susceptible to occlusion and appearance
variations, while wearable sensors can alleviate these challenges by capturing human …

Home action genome: Cooperative compositional action understanding

N Rai, H Chen, J Ji, R Desai… - Proceedings of the …, 2021 - openaccess.thecvf.com
Existing research on action recognition treats activities as monolithic events occurring in
videos. Recently, the benefits of formulating actions as a combination of atomic-actions have …

Multi-gat: A graphical attention-based hierarchical multimodal representation learning approach for human activity recognition

MM Islam, T Iqbal - IEEE Robotics and Automation Letters, 2021 - ieeexplore.ieee.org
Recognizing human activities is one of the crucial capabilities that a robot needs to have to
be useful around people. Although modern robots are equipped with various types of …

ActionSense: A multimodal dataset and recording framework for human activities using wearable sensors in a kitchen environment

J DelPreto, C Liu, Y Luo, M Foshey… - Advances in …, 2022 - proceedings.neurips.cc
This paper introduces ActionSense, a multimodal dataset and recording framework with an
emphasis on wearable sensing in a kitchen environment. It provides rich, synchronized data …

Learning from semantic alignment between unpaired multiviews for egocentric video recognition

Q Wang, L Zhao, L Yuan, T Liu… - Proceedings of the …, 2023 - openaccess.thecvf.com
We are concerned with a challenging scenario in unpaired multiview video learning. In this
case, the model aims to learn comprehensive multiview representations while the cross …