Call for Brave New Ideas
ACM Multimedia is the premier international conference in the area of multimedia within the field of computer science. The 2026 ACM Multimedia Conference takes place in Rio de Janeiro, Brazil — 10–14 November 2026. Multimedia research focuses on technologies that enable the use and exchange of content integrating the multiple perspectives of different digital modalities, including images, text, video, audio, speech, music, and sensor data.
The Brave New Idea (BNI) Track welcomes papers containing original ideas and research visions that draw attention to novel directions in multimedia research. We are particularly calling for papers offering:
- novel, exploratory solutions with sufficient evidence of proof-of-concept;
- visions describing a new or open problem in multimedia research;
- a novel perspective on existing multimedia research;
- connecting old concepts or theories to current development that could lead to new directions.
BNI papers are considered outstanding ACM MM full papers, and accepted BNI papers will appear in the main conference proceedings.
Submission Guidelines
BNI papers are expected to have a high component of novelty. They can also address an understudied, open problem in multimedia, which may receive less attention in the full paper track. However, BNI papers should still support their ideas with sufficient scientific argumentation, and where appropriate experimentation or proof. The papers also require high clarity in presentation.
Submissions must be 6–8 pages in length. For more details on the format, please see the submission instructions in the main conference call for Regular Papers.
Difference between Regular Full Papers and BNI Papers
BNI submissions do not require new empirical results that outperform a state-of-the-art baseline, unlike traditional multimedia submissions. However, BNI submissions that focus on novel, exploratory solutions still need to support their ideas with sufficient experimental evidence that the method works and is not just a wild idea.
BNI submissions that focus on novel perspectives on existing problems, or new research visions do not require empirical results but are still expected to defend their position with solid scientific arguments based on the relevant literature (with a specific focus on a proper and concise literature analysis and discussion). In-depth discussions and explanations of implications are also expected.
Examples of Appropriate BNI Submissions
- Submissions presenting novel, exploratory solutions that have never previously been applied to multimedia tasks.
- Submissions presenting novel solutions from outside the SIGMM community that may enable fundamental, significant advances in multimedia research.
- Research trajectory/agenda for a new and currently unsolved multimedia problem, with a literature study based on a solid exhaustive search protocol demonstrating that it has not been addressed.
- Proposals envision a uniquely different solution for a resolved problem using evidence from the literature (possibly from other disciplines) and/or proof-of-concept.
- A scientific critique of a core assumption underlying multimedia research or systems, supported by relevant literature from other disciplines and/or sufficient experimental evidence.
- Submissions reviving overlooked or “outdated” concepts that become newly relevant due to shifts in hardware, data scale, or practical requirements. For instance, leveraging classic wavelet techniques—once central for image compression—to design hybrid wavelet–neural systems that address today’s efficiency and multi-resolution demands in multimedia applications.
- We particularly encourage concept papers that describe an innovative approach to multimedia, including senses such as taste and smell.
Examples of Inappropriate BNI Submissions
- A submission that is more suitable for the multimedia full paper track.
- A literature review without novel arguments.
- A submission without sufficient connection to multimedia-related topics.
- An opinion piece about a core assumption underlying multimedia research without scientific evidence or support from the relevant literature.
Reviewing Criteria
A separate reviewing committee composed of senior researchers will review the BNI papers. The reviewing will be a similarly rigorous process that all regular papers go through. However, the reviewing criteria will be different from the full paper track, with high scores being assigned to novelty and impact components, while less on the limitations or current performance of the method.
Submissions will be evaluated using the following criteria:
- Novelty: Are people already studying this problem in the multimedia community? In other communities?
- Conceptual leap: How does it change our way of thinking about a problem, a method, or its execution? How much will research in this area advance our state of knowledge?
- Depth of impact: How many supporting sub-problems requiring foundational research might arise from the observations in the submission?
- Breadth of impact: What stakeholders inside or outside of the SIGMM community are impacted? What new applications might this idea trigger?
- Relevance to SIGMM: Who from the SIGMM community might this problem be directly relevant to?
Submission, Desk Reject Criteria and Blinding Policy
We ask all submissions to the BNI Track to follow the main-track Submission, Desk Reject Criteria and Blinding Policy outlined at https://2026.acmmm.org/site/cfp-guidelines.html.
Important Dates: See https://2026.acmmm.org/site/important-dates.html
Desk rejection Criteria specific to this track
| Item | Description |
|---|---|
| Exceeding # submissions / author | Authors submitting more than 10 papers will see their 11th, 12th, etc. submissions (in submission ID order) desk-rejected. Independently of whether or not one of the first 10 submissions is desk rejected for another reason. The limit of 10 submissions applies jointly to the Technical Track, the Brave New Ideas Track, and the Datasets Track. |
Contacts
For any questions, please contact the BNI Chairs at bni-mm26@acmmm.org:
- Qi Wu (Adelaide University)
- Shahram Ghandeharizadeh (University of Southern California)
- Shuqiang Jiang (Chinese Academy of Science)
- Yingli Tian (City University of New York)