[Download: Action samples (15Gb) | Scene samples (25Gb) | Readme | CVPR09 paper ]


 

We provide a dataset with 12 classes of human actions and 10 classes of scenes distributed over 3669 video clips and approximately 20.1 hours of video in total. The dataset intends to provide a comprehensive benchmark for human action recognition in realistic and challenging settings. The dataset is composed of video clips from 69 movies (see the list of movies below). A part of this dataset was originally used in the paper "Actions in Context", Marszałek et al. in Proc. CVPR'09.

Action samples were collected by means of automatic script-to-video alignment in combination with text-based script classification following Laptev at al. CVPR'08. Video samples generated from training movies correspond to the automatic training subset with noisy action labels. Based on this subset we also constructed a clean training subset with action labels manually verified to be correct. We also provide a test subset with manually checked action labels.

Scene classes are selected automatically from scripts such as to maximize co-occurrence with the given action classes and to capture action context as described in Marszałek et al. CVPR'09. Scene video samples are then generated using script-to-video alignment. The labels of test scene samples are manually verified to be correct.

The following tables provide the numbers of video samples in each of the subsets as well as the distributions of class instances in each subset. Note that samples may contain instances of several actions such e.g. kissing and hugging.

 







Download details

The dataset is split in two parts with actions and scene samples respectively:

Hollywood2-actions.tar.gz | ( mirror 1 ) | approx. size: 15Gb | md5sum: 55948d0ef45a569a2134ea44e6f8976c
Hollywood2-scenes.tar.gz | ( mirror 1 ) | approx. size: 25Gb | md5sum: b77f9ffe18ad5ea04957bb4c7725f5ce

Action video samples are provided in directory AVIClips for three subsets according to the table above. The annotation of samples w.r.t. 12 action classes is located in ClipSets directory. Similarly, the video samples and annotations for scene samples are located in AVSClipsScenes and ClipSetsScenes directories respectively.

Example:
The file ClipSets/AnswerPhone_autotrain.txt contains annotation for AnswerPhone action in the automatic training subset with 810 video clips. Each line of the annotation file provides a name of a video sample in AVIClips directory as well as the flag = {1|-1} indicating whether the sample contains AnswerPhone or not. (Our annotation format is similar to PASCAL VOC annotation format for image classification task).

We also provide conditional probability tables for p(scene|action) and p(action|scene) estimated from an independent set of movie scripts and used in "Actions in Context" Marszałek et al. CVPR'09 paper.


Source movies

The 69 movies used to generate clips in this dataset were divided into 33 training movies and 36 test movies as follows.

Training movies:
American Beauty, As Good as It Gets, Being John Malkovich, The Big Lebowski, Bruce Almighty The Butterfly Effect, Capote, Casablanca, Charade, Chasing Amy, The Cider House Rules, Clerks, Crash, Double Indemnity, Forrest Gump, The Godfather, The Graduate, The Hudsucker Proxy, Jackie Brown, Jay and Silent Bob Strike Back, Kids, Legally Blonde, Light Sleeper, Little Miss Sunshine, Living in Oblivion, Lone Star, Men in Black, The Naked City, Pirates of the Caribbean: Dead Man’s Chest, Psycho, Quills, Rear Window, Fight Club.

Test movies:
Big Fish, Bringing Out The Dead, The Crying Game, Dead Poets Society, Erin Brockovich, Fantastic Four, Fargo, Fear and Loathing in Las Vegas, Five Easy Pieces, Gandhi, Gang Related, Get Shorty, The Grapes of Wrath, The Hustler, I Am Sam, Independence Day, Indiana Jones and The Last Crusade, It Happened One Night, It’s aWonderful Life, LA Confidential, The Lord of the Rings: The Fellowship of the Ring, Lost Highway, The Lost Weekend, Midnight Run, Misery, Mission to Mars, Moonstruck, Mumford, The Night of the Hunter, Ninotchka, O Brother Where Art Thou, The Pianist, The Princess Bride, Pulp Fiction, Raising Arizona, Reservoir Dogs.


Citation

Please cite the following paper if using this dataset in your publications:
@InProceedings{marszalek09,
    author = "Marcin Marsza{\l}ek and Ivan Laptev and Cordelia Schmid",
    title = "Actions in Context",
    booktitle = "IEEE Conference on Computer Vision \& Pattern Recognition",
    year = "2009"
}