Welcome to my personal page
I am an AI Research Scientist at Meta AI London, where I work on video diffusion models and generative rendering.
I received my Ph.D. in Computer Science from the University of Surrey, supervised by Prof. Tao Xiang and Prof. Yi-Zhe Song, and worked closely with Dr. Xiatian (Eddy) Zhu.
I completed my Bachelor’s degree in Computer Science (Artificial Intelligence) at the University of Malaya (UM), where I was a lab member of CISIP under Prof. Chan Chee Seng.
You can contact me via kamwoh [at] gmail.com. Please see my CV at here.
My Projects
Generative Rendering
- Kaleido - A family of spatial generative models that achieves photorealistic, unified object- and scene-level neural rendering.
Diffusion Models
- PartCraft (ECCV 2024) - Crafting object by parts with text-to-image diffusion models.
- Chirpy3D - Learning 3D fine-grained object generation from 2D unposed images.
Interpretable Fine-grained Hashing
- ConceptHash (CVPRW 2024 FGVC11 Best paper award) - Learning to encode parts into interpretable codes.
Deep Hashing for Image Retrieval
- DPN (IJCAI 2020) - Bit-wise hinge loss with random orthogonal codebook.
- OrthoHash (NeurIPS 2021) - Cross entropy loss with random orthogonal codebook.
- FIRe - Open source Fast Image Retrieval framework.
- SDC (BMVC 2023 Oral) - Unsupervised hashing by maximizing the utilization of hash spaces through Wasserstein distance.
Deep Watermarking
- DeepIPR (NeurIPS 2019) - Watermarking our DNNs by embedding “passport” and “signature”.
- IPR-GAN (CVPR 2022) - Protecting our GANs by generating watermarked images.
Review Experiences
- NeurIPS 2025
- ICML 2025
- ICLR 2025
- AISTATS 2025
- AAAI 2025
- NeurIPS 2024
- ECCV 2024
- IJCV
- CVPR 2024
- ICLR 2024
- NeurIPS 2023
- CVPR 2023
- AAAI 2023
- ECCV 2022
- CVPR 2022
- ICME 2022
- AAAI 2021
- CVPR 2021