---
title: "ACMMM (A*): papers and universities"
description: "ACMMM (ACM Multimedia) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 2,812 of its papers from 2024–2026 (1,237 in 2024, 1,575 in 2025; 2026 not in OpenAlex yet). By the countries of the authors' institutions, the most papers come from China (2,387), the United States (239) and Singapore (220)."
url: https://scholar4ai.com/proceedings/acmmm
markdown_url: https://scholar4ai.com/proceedings/acmmm.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "ACMMM (ACM Multimedia) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 2,812 of its papers from 2024–2026 (1,237 in 2024, 1,575 in 2025; 2026 not in OpenAlex yet). (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# ACMMM: ACM Multimedia — papers and institutions, 2024–2026

Papers of ACMMM, ACM Multimedia (CORE rank A*; field: Computer vision and multimedia computation), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- ACMMM (ACM Multimedia) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 2,812 of its papers from 2024–2026 (1,237 in 2024, 1,575 in 2025; 2026 not in OpenAlex yet).
- By the countries of the authors' institutions, the most papers come from China (2,387), the United States (239) and Singapore (220).
- The institutions with the most papers are Chinese Academy of Sciences (192), Zhejiang University (169) and Tsinghua University (167).
- Its most-cited paper of these years is “Wave-Mamba: Wavelet State Space Model for Ultra-High-Definition Low-Light Image Enhancement” (2024), with 119 citations.

## Papers per year

*ACMMM papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 1,237 | 1,232 |
| 2025 | 1,575 | 1,561 |
| 2026 | – | – |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4363608757](https://openalex.org/S4363608757) | The conference's proceedings |

## Who publishes there

*Institutions with the most ACMMM papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 192 |
| 2 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 169 |
| 3 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 167 |
| 4 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 149 |
| 5 | [University of Science and Technology of China](https://scholar4ai.com/institutions/university-of-science-and-technology-of-china.md) | 141 |
| 6 | [Shanghai Jiao Tong University](https://scholar4ai.com/institutions/shanghai-jiao-tong-university.md) | 141 |
| 7 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 137 |
| 8 | [Harbin Institute of Technology](https://scholar4ai.com/institutions/harbin-institute-of-technology.md) | 121 |
| 9 | [Fudan University](https://scholar4ai.com/institutions/fudan-university.md) | 108 |
| 10 | [Nanyang Technological University](https://scholar4ai.com/institutions/nanyang-technological-university.md) | 98 |

*Countries with the most ACMMM papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 2,387 |
| 2 | United States | 239 |
| 3 | Singapore | 220 |
| 4 | Hong Kong | 217 |
| 5 | Australia | 159 |
| 6 | United Kingdom | 129 |
| 7 | Japan | 65 |
| 8 | South Korea | 50 |
| 9 | Macao | 42 |
| 10 | Canada | 41 |

*Keywords with the most ACMMM papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | diffusion models | 166 |
| 2 | [vision-language models](https://scholar4ai.com/keywords/vision-language-models.md) | 153 |
| 3 | multimodal large language models | 140 |
| 4 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 135 |
| 5 | [multimodal fusion](https://scholar4ai.com/keywords/multimodal-fusion.md) | 100 |
| 6 | [contrastive learning](https://scholar4ai.com/keywords/contrastive-learning.md) | 84 |
| 7 | CLIP | 75 |
| 8 | [knowledge distillation](https://scholar4ai.com/keywords/knowledge-distillation.md) | 72 |
| 9 | 3D Gaussian Splatting | 71 |
| 10 | text-to-image generation | 57 |

## Most-cited papers

*Most-cited ACMMM papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 119 | [Wave-Mamba: Wavelet State Space Model for Ultra-High-Definition Low-Light Image Enhancement](https://doi.org/10.1145/3664647.3681580) | 2024-10-26 | Wenbin Zou, Hongxia Gao, Weipeng Yang et al. |
| 2 | 116 | [TransNet V2: An Effective Deep Network Architecture for Fast Shot Transition Detection](https://doi.org/10.1145/3664647.3685517) | 2024-10-26 | Tomáš Souček, Jakub Lokoč |
| 3 | 110 | [Making Large Language Models Perform Better in Knowledge Graph Completion](https://doi.org/10.1145/3664647.3681327) | 2024-10-26 | Yichi Zhang, Zhuo Chen, Lingbing Guo et al. |
| 4 | 106 | [Multi-Scale and Detail-Enhanced Segment Anything Model for Salient Object Detection](https://doi.org/10.1145/3664647.3680650) | 2024-10-26 | S. Gao, Pingping Zhang, Tianyu Yan et al. |
| 5 | 101 | [DiffMM: Multi-Modal Diffusion Model for Recommendation](https://doi.org/10.1145/3664647.3681498) | 2024-10-26 | Yangqin Jiang, Lianghao Xia, Wei Wei et al. |
| 6 | 95 | [VLMEvalKit: An Open-Source ToolKit for Evaluating Large Multi-Modality Models](https://doi.org/10.1145/3664647.3685520) | 2024-10-26 | Haodong Duan, Junming Yang, Yuxuan Qiao et al. |
| 7 | 94 | [AbsGS: Recovering Fine Details in 3D Gaussian Splatting](https://doi.org/10.1145/3664647.3681361) | 2024-10-26 | Zongxin Ye, Wenyu Li, Sidun Liu et al. |
| 8 | 91 | [Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model](https://doi.org/10.1145/3664647.3681173) | 2024-10-26 | Xu Han, Yuan Tang, Zhaoxuan Wang et al. |
| 9 | 84 | [Efficient Face Super-Resolution via Wavelet-based Feature Enhancement Network](https://doi.org/10.1145/3664647.3681088) | 2024-10-26 | Wenjie Li, Heng Guo, Xuannan Liu et al. |
| 10 | 78 | [FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining](https://doi.org/10.1145/3664647.3680862) | 2024-10-26 | Zhen Zou, Hu Yu, Jie Huang et al. |

## Cite this page

Scholar4AI. (2026). ACMMM: ACM Multimedia — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/acmmm

```bibtex
@misc{scholar4ai-proceedings-acmmm,
  author = {{Scholar4AI}},
  title = {ACMMM: ACM Multimedia — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/acmmm}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).