Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Features

no code implementations • CVPR 2023 • Fumiaki Sato, Ryo Hachiuma, Taiki Sekii

Particularly, during the training phase using normal samples, the method models the distribution of skeleton features of the normal actions while freezing the weights of the DNNs and estimates the anomaly score using this distribution in the inference phase.

Action Recognition Zero-Shot Learning

Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling

no code implementations • CVPR 2023 • Ryo Hachiuma, Fumiaki Sato, Taiki Sekii

A point cloud deep-learning paradigm is introduced to the action recognition, and a unified framework along with a novel deep neural network architecture called Structured Keypoint Pooling is proposed.

Action Recognition Data Augmentation +5