Demo Data from EDBT 2026 / reviewers in the wild / expert
Minwoo Oh
dblp:402/9904
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 67% Audio and music processing · 33% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 77% Haptics and multimodal interaction · 23% | |
| Network and information security
1 paper |
Digital forensics and information hiding · 100% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia analysis and retrieval
cross-modal retrieval |
0.9 | 1 | 2025 | Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning Pipeline · IJCAI 2025 |
Audio and music processing › source separation
music source separation |
0.9 | 1 | 2025 | Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning Pipeline · IJCAI 2025 |
Multimedia analysis and retrieval › cross-modal retrieval
video-music retrieval |
0.9 | 1 | 2025 | Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning Pipeline · IJCAI 2025 |
Digital forensics and information hiding › copyright protection
copyright infringement detection |
0.3 | 1 | 2025 | Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning Pipeline · IJCAI 2025 |
Methods — techniques the papers use, named apart from their topics
music source separation · 1.7deep learning · 1.7cross-modal video-music retrieval · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning PipelineabstractShort video platforms like YouTube Shorts and TikTok face significant copyright compliance challenges, as infringers frequently embed arbitrary background music (BGM) to obscure original soundtracks (OST) and evade content originality detection. To tackle this issue, we propose a novel pipeline that integrates Music Source Separation (MSS) and cross-modal video-music retrieval (CMVMR). Our approach effectively separates arbitrary BGM from the original OST, enabling the restoration of authentic video audio tracks. To support this work, we introduce two domain-specific datasets: OASD-20K for audio separation and OSVAR-160 for pipeline evaluation. OASD-20K contains 20,000 audio clips featuring mixed BGM and OST pairs, while OSVAR160 is a unique benchmark dataset comprising 1,121 video and mixed-audio pairs, specifically designed for short video restoration tasks. Experimental results demonstrate that our pipeline not only removes arbitrary BGM with high accuracy but also restores OSTs, ensuring content integrity. This approach provides an ethical and scalable solution to copyright challenges in user-generated content on short video platforms. Minwoo Oh, Eunil Park |
IJCAI | 1 |
| 2025 | AttraCar: Multisensory In-Car VR with Thermal, Airflow, and Motion Feedback through Built-In Vehicle Systems
Dohyeon Yeo, Gwangbin Kim, Minwoo Oh, Jeongju Park, Bocheon Gim, Seongjun Kang, Ahmed Elsharkawy 0001, Seungjun Kim 0001 |
UIST | 3 |