We are delighted to welcome you to Ottawa, the heart of Canada, for ACM Multimedia 2023, the 31st ACM International Conference on Multimedia. We pay respect to the Algonquin people, who are the traditional guardians of this land. We acknowledge their longstanding relationship with this territory, which remains unceded. We pay respect to all Indigenous people in this region, from all nations across Canada, who call Ottawa home. We acknowledge the traditional knowledge keepers, both young and old. And we honour their courageous leaders: past, present, and future.
ACM Multimedia is the premier international conference series in the field of multimedia within computer science. Since 1993, ACM Multimedia has been bringing together researchers and practitioners from academia and industry worldwide to present innovative research and discuss recent advancements in multimedia.
In 2023, ACM Multimedia returned to Ottawa for the second time since 2001, featuring an extensive program. This program includes technical sessions covering all aspects of the multimedia field in the form of oral and poster presentations, tutorials, panels, demonstrations, brave new ideas, a doctoral symposium, and workshops. Additionally, there will be Grand Challenge Competitions and Open- Source Software Competitions.
We are excited to host face-to-face gatherings, providing the opportunity to meet colleagues and friends in person. While priority will be given to physical attendees, remote attendees will also enjoy live question-and-answer sessions and presentations from authors via pre-recorded videos. Videos of all papers can be accessed online before the start of the main conference events.
This year, we continued the bold step taken at ACM Multimedia 2020, making ACM Multimedia more open by offering the community the possibility to make the reviewing process of each paper open and transparent. OpenReview was used to implement this vision, and we observed a significant improvement in the overall scientific quality of the conference program.
Cited By
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Rizzi P, Gormish M, Kovarskiy J, Reite A, Zeiler M, Manser K, De Melo C, Rao R and Howell C (2024). Mixing synthetic and real data to build AI vision models Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II, 10.1117/12.3013688, 9781510673885, (43)
- Niu Y, Xing X, Jia Z, Liu R, Xin M and Cui J Diffusion Recommendation with Implicit Sequence Influence Companion Proceedings of the ACM Web Conference 2024, (1719-1725)
Index Terms
- Proceedings of the 31st ACM International Conference on Multimedia
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
MM '24 | 4,385 | 1,150 | 26% |
MM '19 | 936 | 252 | 27% |
MM '18 | 757 | 209 | 28% |
MM '17 | 684 | 189 | 28% |
MM '16 | 237 | 52 | 22% |
MM '15 | 252 | 56 | 22% |
MM '14 | 286 | 55 | 19% |
MM '13 | 235 | 47 | 20% |
MULTIMEDIA '05 | 312 | 49 | 16% |
MULTIMEDIA '02 | 330 | 46 | 14% |
MULTIMEDIA '97 | 142 | 40 | 28% |
Overall | 8,556 | 2,145 | 25% |