Spatio-Temporal Action Localization
13 papers with code • 1 benchmarks • 6 datasets
Latest papers with no code
Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer -- Current Trends and Research Perspectives
Overall, this survey provides a valuable resource for researchers interested in the field of action scene understanding in soccer.
End-to-End Spatio-Temporal Action Localisation with Video Transformers
The most performant spatio-temporal action localisation models use external person proposals and complex external memory banks.
Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling
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.
SEAL: A Large-scale Video Dataset of Multi-grained Spatio-temporally Action Localization
SEAL consists of two kinds of annotations, SEAL Tubes and SEAL Clips.
Relation Modeling in Spatio-Temporal Action Localization
This paper presents our solution to the AVA-Kinetics Crossover Challenge of ActivityNet workshop at CVPR 2021.
Relevance Detection in Cataract Surgery Videos by Spatio-Temporal Action Localization
This module consists of four parallel recurrent CNNs being responsible to detect four relevant phases that have been defined with medical experts.
Real-time Spatio-temporal Action Localization via Learning Motion Representation
In this paper, we exploit better ways to use motion information in a unified end-to-end trainable network architecture.
Unsupervised Domain Adaptation for Spatio-Temporal Action Localization
Spatio-temporal action localization is an important problem in computer vision that involves detecting where and when activities occur, and therefore requires modeling of both spatial and temporal features.
CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization
Most current pipelines for spatio-temporal action localization connect frame-wise or clip-wise detection results to generate action proposals, where only local information is exploited and the efficiency is hindered by dense per-frame localization.
Three Branches: Detecting Actions With Richer Features
We present our three branch solutions for International Challenge on Activity Recognition at CVPR2019.