Zetao Feng (冯则涛)

I am a PhD student at CDT in Foundational AI at University College London, supervised by Prof. Lourdes Agapito. My research topic is Neural Surface Reconstruction from Video. Prior to start my PhD, I obtain an MSc degree at UCL and a bachelor degree at joint degree programme between QMUL and BUPT, worked with Prof. Changejae Oh.

Email  /  CV  /  Google Scholar  /  Linkedin  /  Github

I'm interested in computer vision, image processing, and machine learning related areas.

We propose MorpheuS, a dynamic scene reconstruction method that leverages neural implicit representations and diffusion priors for achieving 360° reconstruction of a moving object from a monocular RGB-D video.

We present a neural RGB-D SLAM system, Co-SLAM, which performs robust camera tracking and high-fidelity surface reconstruction in real time. This paper extends the work presented in my MSc thesis.

We present a refinement framework to boost the performance of pre-trained semi-supervised video object segmentation (VOS) models based on scale inconsistency. Our work consists of a multi-scale attention module with the corresponding self-supervised online adaptation strategy.

We use a MobileNet as a backbone model to estimate the phyiscal physical properties of house-hold containers and their fillings. A data augmentation strategy with consistency measurement is proposed to improve the generalization ability of our model.

• Journal Reviewer: RA-L
• Teaching assistant: Machine Vision, Image Processing