Mar 31, 2023 · Since the zero-shot learning method can realize the recognition of unseen action categories without relying on a large amount of labeled data.

At present, the research on human action recognition has achieved remarkable results and is widely used in various industries. Among them, human action ...

The proposed approach significantly outperforms the state of the arts in zero-shot action recognition in terms of the the top-1 accuracy on UCF-101, HMDB-51 and ...

Oct 23, 2024 · Video understanding has long suffered from reliance on large labeled datasets, motivating research into zero-shot learning.

Zero-shot learning consists in learning how to recognise new concepts by just having a description of them. 1.

Mar 27, 2023 · This study investigates unsupervised anomaly action recognition, which identifies video-level abnormal-human-behavior events in an unsupervised manner without ...

For example, if a person is familiar with ice skating and understands the concept of dancing, (s)he will have no trouble recognizing the action of ice dancing.

Zero short learning primarily uses data that is synthesized to compensate for lack of training examples. In this paper, two different approaches are proposed ...

However, we evaluate our method using the top-1 and top-5 accuracy since the purpose of this work is to create a strong zero-shot classifier rather than learn a ...

Recently, with the ever-growing action categories, zero-shot action recognition (ZSAR) has been achieved by automat- ically mining the underlying concepts ...