Dataset release for our paper published at CVPR 2018.
📜 MovieGraphs: Towards Understanding Human-Centric Situations from Videos
- March 2019 (Original release with python 2.7; shared over emails)
- June 2025 (python 3.10 support)
- dvds.txt: links to Amazon DVDs
- movies_list.txt: just a list of movies
- split.json: train/validation/test splits
- xxx: scene id, starting from 1
- yyyy: start shot for scene xxx starting from 1
- zzzz: end shot for scene xxx
- moviegraphs_startend_frames: first and last frame of every movie scene clip (tarball, please expand)
- shot boundaries (videvents) and scene GT boundaries
- py3loader_new
all_movies.pkl: main pickle file containing the parsed graph annotations.GraphClasses.py: main ClipGraph and MovieGraph python classes. There are many helper functions here, please read this.startup.py: a little test to make sure everything is setup correctly. This should run without errors.tutorial.ipynb: a small notebook that tests functionality of some parts ofGraphClasses.py. If you run all cells, it should create a pdf file with all graphs of one movie.
- nx_code: copies and updates essential files from
networkx=1.10that were required forGraphClasses.pyto work properly withpython 3.
dvds.txt. If you intend to use the dataset for non-commercial and academic research purposes, a 1 fps version can be downloaded here.
Subtitles can be downloaded here.
Worked with py2.7 and networkx1.10
- py3loader
- 2017-11-02-51-7637_py3.pkl: main pickle file containing the parsed graph annotations
- GraphClasses.py: main ClipGraph and MovieGraph python classes
- startup.py: a little test file to make sure things are working as expected
Thanks to Lakshmipathi Balaji for helping with the new release!