{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/avid-dataset-anonymized-videos-from-diverse","title":"AViD Dataset: Anonymized Videos from Diverse Countries","arxiv_id":"2007.05515","date":"2020-07-10","proceeding":"NeurIPS 2020 12","authors":["AJ Piergiovanni","Michael S. Ryoo"],"abstract":"We introduce a new public video dataset for action recognition: Anonymized Videos from Diverse countries (AViD). Unlike existing public video datasets, AViD is a collection of action videos from many different countries. The motivation is to create a public dataset that would benefit training and pretraining of action recognition models for everybody, rather than making it useful for limited countries. Further, all the face identities in the AViD videos are properly anonymized to protect their privacy. It also is a static dataset where each video is licensed with the creative commons license. We confirm that most of the existing video datasets are statistically biased to only capture action videos from a limited number of countries. We experimentally illustrate that models trained with such biased datasets do not transfer perfectly to action videos from the other countries, and show that AViD addresses such problem. We also confirm that the new AViD dataset could serve as a good dataset for pretraining the models, performing comparably or better than prior datasets.","url_abs":"https://arxiv.org/abs/2007.05515v3","url_pdf":"https://arxiv.org/pdf/2007.05515v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"avid-dataset-anonymized-videos-from-diverse","repo_url":"https://github.com/piergiaj/AViD","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"action-classification","task_name":"Action Classification"},{"task_slug":"action-detection","task_name":"Action Detection"},{"task_slug":"action-recognition-in-videos","task_name":"Action Recognition"}],"methods":[],"datasets_introduced":[{"slug":"avid","name":"AViD","full_name":""}],"methods_introduced":[],"results":[{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"SlowFast-101 16x8","rank_in_archive_order":2,"of":10,"metrics":{"Accuracy":"50.9"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"RepFlow ResNet-50","rank_in_archive_order":3,"of":10,"metrics":{"Accuracy":"50.5"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"SlowFast-50 8x8","rank_in_archive_order":4,"of":10,"metrics":{"Accuracy":"50.4"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"Two-Stream 3D ResNet-50","rank_in_archive_order":5,"of":10,"metrics":{"Accuracy":"50.1"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"(2+1)D ResNet-50","rank_in_archive_order":6,"of":10,"metrics":{"Accuracy":"48.8"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"SlowFast-50 4x4","rank_in_archive_order":7,"of":10,"metrics":{"Accuracy":"48.5"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"3D ResNet-50","rank_in_archive_order":8,"of":10,"metrics":{"Accuracy":"48.2"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"I3D","rank_in_archive_order":9,"of":10,"metrics":{"Accuracy":"46.8"},"uses_additional_data":false},{"leaderboard":"/sota/action-classification-on-avid","task":"Action Classification","dataset":"AViD","model":"2D ResNet-50","rank_in_archive_order":10,"of":10,"metrics":{"Accuracy":"36.2"},"uses_additional_data":false},{"leaderboard":"/sota/action-detection-on-charades","task":"Action Detection","dataset":"Charades","model":"3D ResNet-50 + super-events pretrained on AViD","rank_in_archive_order":8,"of":16,"metrics":{"mAP":"25.2"},"uses_additional_data":true},{"leaderboard":"/sota/action-detection-on-charades","task":"Action Detection","dataset":"Charades","model":"3D ResNet-50 pretrained on AViD","rank_in_archive_order":12,"of":16,"metrics":{"mAP":"23.2"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2007.05515","atlas_url":"https://app.syntology.ai/?focus=2007.05515","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}