Research Materials

This is where we will keep track of resources we deem to be important.

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Data Sources

Links for important and useful publicly available datasets.

VideoDatasets
AMASS
- AMASS is a large database of human motion unifying different optical marker-based motion capture datasets by representing them within a common framework and parameterization. AMASS is readily useful for animation, visualization, and generating training data for deep learning.
How-to-100m
- HowTo100M is a large-scale dataset of narrated videos with an emphasis on instructional videos where content creators teach complex tasks with an explicit intention of explaining the visual content on screen. HowTo100M features a total of 136M video clips with captions sourced from 1.2M Youtube videos (15 years of video) 23k activities from domains such as cooking, hand crafting, personal care, gardening or fitness
YouTube-100M
- The YouTube-100M data set consists of 100 million YouTube videos: 70M training videos, 10M evaluation videos, and 20M validation videos.
- YouTube-8M
  - The YouTube-8M Segments dataset is an extension of the YouTube-8M dataset with human-verified segment annotations. In addition to annotating videos, we would like to temporally localize the entities in the videos, i.e., find out when the entities occur.
- HMDB: a large human motion database
  - About 2GB for a total of 7,000 clips distributed in 51 action classes.
    Stabilized HMDB51 – the number of clips and classes are the same as HMDB51, but there is a mask in [video_name].form associated with each clip. The mask file is readable in matlab.