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Found 5 papers, 0 papers with code
SegLoc: Visual Self-supervised Learning Scheme for Dense Prediction Tasks of Security Inspection X-ray Images
Thus, here, we have considered dense prediction tasks on security inspection x-ray images to evaluate our proposed model Segmentation Localization (SegLoc).
Reinforcement Learning-based Mixture of Vision Transformers for Video Violence Recognition
The empirical results show the proposed MoE architecture's superiority over CNN-based models by achieving 92. 4% accuracy on the RWF dataset.
Video Violence Recognition and Localization Using a Semi-Supervised Hard Attention Model
The proposed model achieved state-of-the-art accuracy of 90. 4% and 98. 7% on RWF and Hockey datasets, respectively.
Ranked #2 on
Activity Recognition
on RWF-2000
(using extra training data)
Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks
This paper presents a novel method of adversarial knowledge transfer named SA-GAN stands for Subject Adaptor GAN which utilizes Generative Adversarial Network framework to perform cross-subject transfer learning in the domain of wearable sensor-based Human Activity Recognition.
Generative Adversarial Network
Human Activity Recognition
+2
Online Human Activity Recognition Employing Hierarchical Hidden Markov Models
After detecting the activity pane, the predicted label will be corrected utilizing statistical features such as time of day at which the activity happened and the duration of the activity.
