Media
With the rapid increase in volume and variety of user generated content on the web, the way that people seek and consume information and knowledge is changing.
Besides conducting research on multimedia technologies, we also design exciting new ways to experience and interact with content involving various media – from video games to smart glasses and sketch animation interfaces.
What We Do
Sub Areas
- Computer Audition
- Computer Graphics
- Computational Geometry
- Computer Vision & Pattern Recognition
- Human-Computer Interaction
- Multimedia Analytics
- Multimedia Search & Recommendation
- Multimedia Security & Privacy
- Multimedia Signal Processing
- Multimedia Systems
- Natural Language Processing
- Social Media Analysis
- Sound & Music Computing
- Ubiquitous Computing
- Visualisation
Our Research Projects
DroneBuddy: Drone as a Companion for People with Visual Impairments
OOI Wei Tsang, Suranga Chandima NANAYAKKARA
Drones has potential as assistive devices for people with visual impairments (PVI), for tasks such as locating personal items. The DroneBuddy project aims to develop interaction techniques, for a PVI to interact with and customize a drone equipped with programmable APIs to perform a personalized task.
- Human-Computer Interaction
Acquiring High Quality Datasets for Dynamic Scene Reconstruction and Event Cameras in Motions
The project addresses limitations in reconstructing dynamic 3D scenes and static scenes from event cameras. It aims to acquire datasets for indoor scenes with moving objects and high-speed rendering, advancing neural scene representation in these scenarios through public release.
Towards Controllable Generation for Scientific Document Summarization
This project enhances scientific document summarization by using scientific claims as constraints, improving summarization quality and user control. It integrates claim representation into seq2seq models like BART and T5, aiming for topic-based evaluation and plans to publish three works and deliver a practical toolkit.
Real-time Distributed Hybrid Rendering with 5G Edge Computing for Realistic Graphics in Mobile Games and Metaverse Applications
DHR improves mobile/metaverse graphics using distributed hybrid rendering through cloud servers and thin clients. Aided by 5G edge computing, it aims to outperform traditional methods in visuals and performance, providing an open-source engine.
NUS Digital Twin for Research and Services
HUANG Zhiyong, HE Bingsheng, Anthony TUNG
This project aims to create a virtual twin of the NUS campus integrating the built and natural environment with static and dynamic data for modelling, visualization, simulation, analysis and AI. By creating a high-fidelity model, it harmonizes diverse data sources, optimizing performance for applications including smart transport, utility planning, climate studies and sustainable campus design.
DesCartes WP4: Human-AI Collaboration
OOI Wei Tsang, Brian LIM, ZHAO Shengdong
WP4 focuses on how humans can interact with AI to (i) bring humanity aspects that cannot be computationally modeled into AI systems and algorithms, forming a hybrid AI with human interaction at its core, and (ii) allow hybrid AI to augment human perception and cognition (especially assisting humans in decision-making). Within this WP, we propose to develop interaction and visualization techniques
Recommendation Systems
Recommendations Systems curate our news feeds, and show products for us to buy, shows to watch and music to listen to. Our work examines the use of temporal and prerequisite constraints in improving recommendation systems quality in sparse data application areas, such as module and course recommendation.
Task Oriented Dialogue Systems
We now use voice- and text-enabled chatbots and dialogue systems often to accomplish tasks. We examine ways to improve such systems by incorporating everyday knowledge in the form of knowledge graphs and incorporating means to adapt trained systems to new domain application areas.
Scholarly Document Information Extraction
Particular components of scholarly documents have different uses and can be extracted and analysed to help improve the speed and quality of scientific discovery. These include better understanding of the topics, problems, approaches, evaluation metrics, tools and datasets used in research. Extracting such data from natural language text allows computational analyses of works at a large scale.
Adversarial Attack and Defence on Fake Imagery Detectors
- Computer Vision & Pattern Recognition
Our Research Groups
Web, Information Retrieval, Natural Language Processing Group (WING)
Min leads WING, a group of postgraduate and undergraduate researchers examining issues in digital libraries, information retrieval and natural language processing research. Find out more at http://wing.comp.nus.edu.sg.
AI for Social Good Group
AI4SG (AI for Social Good) lab focus on designing artificial intelligence (AI) technologies for social good. We believe that AI technologies have strong potential to bring benefits to our society.