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1
Introduction
2
Motivation
3
Datasets
4
Datasets for Video Class
5
Data Collection Pipeline
6
Training and Validation
7
Negative Samples
8
Internal Deduplication
9
Human Action Detection
10
Flowchart
11
Classifiers
12
YouTube Frame Based
13
Google Image Based
14
Sampling Distribution
15
Quality Control
16
Validation
17
Comparison
18
Evaluation
Description:
Explore a comprehensive overview of the Sparsely Labeled Dataset for Action Classification and Localization (SLAC) in this 36-minute lecture from the University of Central Florida. Delve into the motivation behind the dataset's creation, understand the data collection pipeline, and learn about the various classifiers used. Examine the sampling distribution, quality control measures, and validation processes employed. Compare SLAC with other datasets and gain insights into its evaluation methods for human action detection and classification in videos.

A Sparsely Labeled Dataset for Action Classification and Localization - SLAC

University of Central Florida
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