Leaderboard submissions for the Activity-Classification task are now closed. Thanks to all participating teams !
Large scale activity recognition has made remarkable progress driven by the curation of large scale labeled video datasets. Evaluation tasks in these datasets include activity classification, activity and object detection and localization, action prediction, episodic memory for object instance retrieval, object interactions with hands/tools/people, speaker prediction and scene diarization in long duration videos.
However, performance on these important tasks remains limited by the scale, quality and applicability of data. While there are many large-scale video datasets for pretraining activity recognition, these datasets are nearly all scraped from social media platforms such as YouTube or Instagram. The activities in these datasets do not reflect true diversity of activities in the real world, and instead represent a biased and unbalanced sample of labels that are interesting enough for social media. Specifically, these datasets lack coverage of:
Our goal is to bring together researchers interested in the problem of activity recognition of common, fine and diverse human activities. We will provide a forum for discussion, and provide a new large-scale training/validation/test set of fine-grained activities collected from around the world to focus discussion and characterize progress in this emerging research field.
We will have three invited keynote talks from experts in the field. We will also have two talks from the top performers on the Open Fine-grained Activity Detection (OpenFAD) Activity Classification challenge that uses the Consented Activities of People (CAP) dataset. We will select paper submissions to be published in the WACV’23 proceedings after a double-blind review on topics related to activity classification and detection. The workshop will provide a platform for researchers to share research experiences and foster collaboration.
A one day workshop on Fine Grained Activity Detection to be held on January 7, 2023 at the 2023 IEEE Winter Conference on Applications of Computer Vision (WACV’23) in Waikoloa, Hawaii.
Every day, humans perform many closely related activities that involve subtle discriminative motions, such as putting on a shirt vs. putting on a jacket, or shaking hands vs. giving a high five. Activity recognition by ethical visual AI could provide insights into our patterns of dailylife, however existing activity recognition datasets do not capture the massive diversity of these human activities around the world. The goal of this workshop is to bring together research the representation and recognition of fine grained activities of daily life around the world, and provide a forum for researchers to share expertise on this emerging problem.
The workshop will host the first Open Fine-grained Activity Detection (OpenFAD) Challenge. OpenFAD is an activity classification and detection evaluation to measure how well systems can automatically classify or temporally detect fine-grained activities collected from handheld devices. This challenge uses the Consented Activities of People (CAP) dataset which is a new dataset of 1.45M videos of 512 fine grained activity classes of consented people. We will host a leaderboard for the Activity Classification (AC) submission track to characterize the state-of-the-art on fine grained activity classification on this new dataset. The leaderboard evaluation will be performed on a video test set available to the challenge participants, with sequestered ground truth.
Accepted papers will be published in the workshop proceedings, and the top two teams on the leaderboard will be invited to give a talk.
|September 5, 2022||AC leaderboard opens|
|December 2, 2022||AC submission deadline|
|December 15, 2022||AC final report available (top-performers notification)|
|January 7, 2023||FGAD’23 Workshop at WACV2023|
|9:00 - 9:05 am||Workshop introduction|
|9:05 - 9:45 am||OpenFAD Challenge overview|
|9:45 - 10:30 am||Invited talk: Hilde Kuehne (Goethe U. Frankfurt)|
|10:30 - 10:45 am||Coffee break|
|10:45 - 11:30 am||Invited talk: Jeffrey Byrne (Visym Labs)|
|11:30 - 12:15 pm||OpenFAD Challenge results: Jon Fiscus (NIST)|
|12:00 - 1:30 pm||Lunch|
|1:30 - 2:00 pm||Challenge Winner talk (BUPT-MCPRL)|
|2:00 - 2:45 pm||Invited talk: Yogesh S. Rawat (UCF)|
|2:45 - 3:00 pm||Q&A and wrapup|
Authors are invited to submit original work not currently under consideration elsewhere. The FGAD’23 workshop submissions will be handled via the CMT review site.
Accepted papers will be allocated 8 pages in the proceedings (a paper can be up to 8 pages + the references). The manuscripts should be submitted in PDF format and should follow the requirements of the IEEE WACV paper format. All work submitted to WACV workshop is considered confidential until the papers appear. Accepted papers will be included in the Proceedings of IEEE WACV 2023 & Workshops and will be sent for inclusion into the IEEE Xplore digital library. The author toolkit is available both on Overleaf and Github, and papers will be submitted via CMT. For more details, please refer to the following documents:
You will be able to register for the FGAD'23 workshop soon.