Oct 13, 2020 · We propose a novel few-shot action recognition framework that uses long short-term memory following 3D convolutional layers for sequence modeling and alignment.

We propose a novel few-shot action recognition framework that uses long short-term memory following 3D convolutional layers for sequence modeling and alignment.

We propose a novel few-shot action recognition framework that uses long short-term memory following 3D convolutional layers for sequence modeling and alignment.

Oct 13, 2020 · This paper proposes Compromised Metric via Optimal Transport (CMOT) to combine the advantages of these two solutions, and amend the ground ...

Few-shot action recognition with implicit temporal alignment and pair similarity optimization. https://doi.org/10.1016/j.cviu.2021.103250.

Jul 20, 2024 · Few-shot action recognition aims to address the high cost and impracticality of manually labeling complex and variable video data in action recognition.

Our main idea is to introduce an implicit temporal align- ment for a video pair, capable of estimating the similarity between them in an accurate and robust.

Aug 4, 2022 · Few-shot action recognition aims to learn a classification model with good generalisation ability when trained with only a few labelled ...

Our main idea is to introduce an implicit temporal alignment for a video pair, capable of estimating the similarity between them in an accurate and robust ...

Oct 28, 2024 · Existing works in few-shot action recognition mostly fine-tune a pre-trained image model and design sophisticated temporal alignment modules ...