YH Technologies at ActivityNet Challenge 2018

2018/06/29 by Ting Yao, Xue Li, Yao, Ting +1 · 1 citation
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Multimodal Machine Learning Applications #Video Analysis and Summarization

paper · pdf · doi:10.48550/arxiv.1807.00686

openalex publication_date 2018/06/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This notebook paper presents an overview and comparative analysis of our systems designed for the following five tasks in ActivityNet Challenge 2018: temporal action proposals, temporal action localization, dense-captioning events in videos, trimmed action recognition, and spatio-temporal action localization.

Citations

• A Pursuit of Temporal Accuracy in General Activity Detection
• The Kinetics Human Action Video Dataset
• Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks
• Deformable Convolutional Networks

Cited by

• StNet: Local and Global Spatial-Temporal Modeling for Action Recognition

Related

• Trimmed Action Recognition, Dense-Captioning Events in Videos, and Spatio-temporal Action Localization with Focus on ActivityNet Challenge 2019
• The ActivityNet Large-Scale Activity Recognition Challenge 2018 Summary
• Technical Report for ActivityNet Challenge 2022 -- Temporal Action Localization
• Temporal Fusion Network for Temporal Action Localization:Submission to ActivityNet Challenge 2020 (Task E)
• Diagnosing Error in Temporal Action Detectors