Many recent breakthroughs in machine learning and machine perception have come from the availability of large labeled datasets, such as ImageNet, which has millions of images labeled with thousands of classes, and has significantly accelerated research in image understanding. Google announced the YouTube-8M dataset in 2016, which spans millions of videos labeled with thousands of classes, with the hope that it would spur similar innovation and advancement in video understanding. YouTube-8M represents a cross-section of our society, and was designed with scale and diversity in mind so that lessons we learn on this dataset can transfer to all areas of our lives, from learning, to communication, to entertainment. It covers over 20 broad domains of video content, including entertainment, sports, commerce, hobbies, science, news, jobs & education, health.
Continuing from the last year's challenge and workshop, we are excited to announce the 2nd Workshop on YouTube-8M Large-Scale Video Understanding, to be held on September 9, 2018, at the European Conference on Computer Vision (ECCV 2018) in Munich, Germany. We invite researchers to participate in this large-scale video classification challenge and to report their results at the workshop, as well as to submit papers describing research, experiments, or applications based on YouTube-8M. The classification challenge will be hosted as a kaggle.com competition. We will feature $5,000 travel award for the 5 top-performing teams (details here).
|9:00 - 9:05||Opening Remarks||Paul Natsev|
|9:05 - 9:30||Overview of YouTube-8M Dataset, Challenge||Challenge Orgnizers|
|9:30 - 10:00||Invited Talk 1: Title TBD||Andrew Zisserman|
|10:00 - 10:30||Invited Talk 2: Title TBD||Rene Vidal|
|10:30 - 10:45||Coffee Break|
|10:45 - 12:00||
Oral Session 1
|12:00 - 1:00||Lunch on your own|
|1:00 - 1:30||Invited Talk 3: Title TBD||Josef Sivic|
|1:30 - 2:00||Invited Talk 4: Title TBD||Manohar Paluri|
|2:00 - 2:30||YouTube-8M Classification Challenge Summary, Organizers' Lightning Talks||Challenge Organizers|
|2:30 - 3:30||Poster Session||Participants|
|3:30 - 3:45||Coffee Break|
|3:45 - 5:00||
Oral Session 2
|5:00 - 5:20||Closing and Award Ceremony||Paul Natsev|
This track will be organized as a Kaggle competition for large-scale video classification based on the YouTube-8M dataset. Researchers are invited to participate in the classification challenge by training a model on the public YouTube-8M training and validation sets and submitting video classification results on a blind test set. Unlike last year, you're challenged to produce a compact video classification model. Your model size must not exceed 1 GB (this is strictly enforced, through model upload). In addition, you are encouraged to have a small bottleneck layer. For example, can you encode the semantic labels by passing-through 100 bytes per video? Even though this is not strictly enforced, it is desired and if followed, should be clearly noted in the paper submission. Open-source TensorFlow code, implementing a few baseline classification models for YouTube-8M, along with training and evaluation scripts, is available at Github. For details on getting started with local or cloud-based training, please see our README and the getting started guide on Kaggle. Results will be scored by a Kaggle evaluation server and published on a public leaderboard, updated live for all submissions (scored on a portion of the test set), along with a final (private) leaderboard, published after the competition is closed (scored on the rest of the test set). Top-ranking submissions in the challenge leaderboard will be invited to the workshop to present their method. Please see details on the Kaggle competition page.
We encourage participants to explore the following topics (non-exhaustive list) and to submit papers to this workshop discussing their approaches and result analysis (publication is also a requirement for prize eligibility on the Kaggle competition):
Researchers are invited to submit any papers involving research, experimentation, or applications on the YouTube-8M dataset. Paper submissions will be reviewed by the workshop organizers and accepted papers will be invited for oral or poster presentations at the workshop.
We encourage participants to explore any relevant topics of interest using YouTube-8M dataset, including but not limited to:
Submission to this track does not require participation in the challenge task, but must be related to the YouTube-8M dataset. We welcome new applications that we didn't think of! Paper submissions are expected to have 8 to 12 pages (no strict page limit) in the ECCV formatting style. Demo paper submissions are also welcome.
All submissions will be handled electronically, through our CMT submission cite. There is no strict limit on the number of pages---we recommend 8 to 12 pages, in the ECCV formatting style. Submission of supplementary material will not be reviewed or considered. Please refer to the files in the Author Guidelines page at the ECCV 2018 website for formatting instructions.
Submitted papers will be reviewed by the organizing committee members, and a subset will be selected for oral or poster presentation. Submissions will be evaluated in terms of potential impact (e.g. performance on the classification challenge), technical depth & scalability, novelty, and presentation.
We do not require blind submissions---author names and affiliations may be shown. We do not restrict submissions of relevant work that is under review or will be published elsewhere. Previously published work is also acceptable as long as it is retargeted towards YouTube-8M. There is no strict page limit but we encourage 8 to 12 page submissions. The accepted papers will be linked on the workshop website and will appear in the official ECCV proceedings.
|Challenge submission (model upload) deadline||August 6, 2018|
|Paper submission deadline & Winners' obligations deadline||August 13, 2018|
|Paper Acceptance Notification & Challenge Winners Confirmation||August 22, 2018|
|Workshop date (co-located with ECCV'18)||September 9, 2018|
|Paper camera-ready deadline||September, 2018 (after the workshop, TBA)|
All deadlines are at 11:59 PM UTC/GMT (4:59 PM PDT).