AAAI 2023technical3 citations

Two-Streams: Dark and Light Networks with Graph Convolution for Action Recognition from Dark Videos (Student Abstract)

Saurabh Suman, Nilay Naharas, Badri Narayan Subudhi, Vinit Jakhetiya

Abstract

In this article, we propose a two-stream action recognition technique for recognizing human actions from dark videos. The proposed action recognition network consists of an image enhancement network with Self-Calibrated Illumination (SCI) module, followed by a two-stream action recognition network. We have used R(2+1)D as a feature extractor for both streams with shared weights. Graph Convolutional Network (GCN), a temporal graph encoder is utilized to enhance the obtained features which are then further fed to a classification head to recognize the actions in a video. The experimental results are presented on the recent benchmark ``ARID" dark-video database.

BibTeX
@article{Suman_Naharas_Subudhi_Jakhetiya_2024, title={Two-Streams: Dark and Light Networks with Graph Convolution for Action Recognition from Dark Videos (Student Abstract)}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/27030}, DOI={10.1609/aaai.v37i13.27030}, abstractNote={In this article, we propose a two-stream action recognition technique for recognizing human actions from dark videos. The proposed action recognition network consists of an image enhancement network with Self-Calibrated Illumination (SCI) module, followed by a two-stream action recognition network. We have used R(2+1)D as a feature extractor for both streams with shared weights. Graph Convolutional Network (GCN), a temporal graph encoder is utilized to enhance the obtained features which are then further fed to a classification head to recognize the actions in a video. The experimental results are presented on the recent benchmark ``ARID" dark-video database.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Suman, Saurabh and Naharas, Nilay and Subudhi, Badri Narayan and Jakhetiya, Vinit}, year={2024}, month={Jul.}, pages={16340-16341} }