Outputs (2)

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Presentation / Conference Contribution
Bond-Taylor, S., Hessey, P., Sasaki, H., Breckon, T., & Willcocks, C. (2022, October). Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes. Presented at ECCV 2022: European Conference on Computer Vision, Tel Aviv, Israel

Whilst diffusion probabilistic models can generate high quality image content, key limitations remain in terms of both generating high-resolution imagery and their associated high computational requirements. Recent Vector-Quantized image models have... Read More about Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes.

Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking
Presentation / Conference Contribution
Leach, A., Rudden, L. S., Bond-Taylor, S., Brigham, J. C., Degiacomi, M. T., & Willcocks, C. G. (2020, December). Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking. Presented at 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)

This paper presents an algorithm, similar to implicit sphere tracing, that ray marches 3D non-convex shapes for efficient collision detection. Instead of finding points on the surface where individual rays strike, an entire shape is marched in unison... Read More about Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking.