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Found 9 papers, 4 papers with code
Activity-Biometrics: Person Identification from Daily Activities
Furthermore, we extensively compare ABNet with existing works in person identification and demonstrate its effectiveness for activity-based biometrics across all five datasets.
Semi-supervised Active Learning for Video Action Detection
First, we demonstrate its effectiveness on video action detection where the proposed approach outperforms prior works in semi-supervised and weakly-supervised learning along with several baseline approaches in both UCF101-24 and JHMDB-21.
PRAT: PRofiling Adversarial aTtacks
Inspired by this, we introduce a novel problem of PRofiling Adversarial aTtacks (PRAT).
Efficiently Robustify Pre-trained Models
A recent trend in deep learning algorithms has been towards training large scale models, having high parameter count and trained on big dataset.
A Large-Scale Analysis on Self-Supervised Video Representation Learning
In this work, we first provide a benchmark that enables a comparison of existing approaches on the same ground.
Ranked #3 on
Self-Supervised Action Recognition
on UCF101
Probing Conceptual Understanding of Large Visual-Language Models
In recent years large visual-language (V+L) models have achieved great success in various downstream tasks.
Video Action Detection: Analysing Limitations and Challenges
Beyond possessing large enough size to feed data hungry machines (eg, transformers), what attributes measure the quality of a dataset?
End-to-End Semi-Supervised Learning for Video Action Detection
In this work, we focus on semi-supervised learning for video action detection which utilizes both labeled as well as unlabeled data.
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos
For tubelet extraction, we propose a localization network which takes a video clip as input and spatio-temporally detects potential foreground regions at multiple scales to generate action tubelets.
