Hence we propose a framework to jointly learn interactions and actions by designing a potential function using both features learned via deep neural networks ...
Hence we propose a framework to jointly learn interaction- s and actions by designing a potential function using both features learned via deep neural networks ...
This work proposes a framework to jointly learn interactions and actions by designing a potential function using both features learned via deep neural ...
Aiming at learning discriminative relation between joints, this paper proposes a joint spatial-temporal reasoning (JSTR) framework to recognize action from ...
Bibliographic details on Joint label-interaction learning for human action recognition.
Dec 10, 2018 · We now review two important approaches for human action recognition, where interactions are either constructed based on heuristic rules or ...
Aiming at learning discriminative relation between joints, this paper proposes a joint spatial-temporal reasoning (JSTR) framework to recognize action from ...
In this paper, we formulate a real-world human action recognition task as a multi-label zero-shot learning problem.
Missing: interaction | Show results with:interaction
Jul 15, 2023 · Specifically, CMAL learns single-stream representation by cross-model adversarial loss to obtain more discriminative features. To aggregate and ...
In this paper, we propose a novel action recognition method that simultaneously learns middle-level representation and classifier by jointly training a ...