AI-based Multi-modal 3D Environment Model Reconstruction

Computer Vision is one of the most active areas where artificial intelligence (AI) is being used. This area is extremely expanding and getting a lot of interests and investments these days. Active perception of a surrounding environment through AI relies heavily on the design of architectures and their extensive training to generate compact representations. Taking advantages of recent advancements in deep learning, these representations have shown significant improvement in building new knowledge and acquiring new skills for AI agents and practical applications in our daily life.

Scene understanding studies the task of representing a captured scene in a manner emulating human-like understanding of that space. Attaining this understanding is crucial for applications such as robotics, tele-communication, smart home, healthcare and assisted living.

In this project, several PhD students are working on a pipeline for modelling and rendering of the full environment including 3D geometry, semantic objects and material attributes from multi-modal inputs such as video, audio and text. You will join this team and investigate topics in AI-based multi-modal 3D environment model reconstruction.

Please contact Dr. Hansung Kim asap, Email: [email protected]

Entry Requirements

All applicants are required to have a first class honours degree (or equivalent) with some further requirements for non-native English speakers. Applicants without MSc or MEng in computer vision or machine learning would have to provide strong justification that they would be able to complete a PhD in this field.

Essential selection criteria include:

• Prior knowledge in computer vision and machine learning.
• Proficiency in Python

Desirable selection criteria include:

• Experience in C++
• Experience in camera or VR systems

Start Date

27^th January 2025 for the home student scholarship / Jan, Apr or June 2025 for self-funded.

Closing date: 31^st December 2024. for the home student scholarship. There is no hard deadline for self-funded. Applications will be considered in the order that they are received, the position will be considered filled when a suitable candidate has been identified.

Funding: Funding for tuition fees and a living stipend are available for a UK home student. We also welcome self-funded international students (Other research expenses will be supported from the project). No scholarship available for international students.

How to apply

Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk)Select programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “PhD Computer Science (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Hansung Kim

Applications should include:

Research Proposal

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

For further information please contact: [email protected]

The School of Electronics & Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.