no code implementations • 9 Apr 2024 • Seunghoi Kim, Chen Jin, Tom Diethe, Matteo Figini, Henry F. J. Tregidgo, Asher Mullokandov, Philip Teare, Daniel C. Alexander
We hypothesize such hallucinations result from local OOD regions in the conditional images.
1 code implementation • 11 Nov 2023 • Seunghoi Kim, Henry F. J. Tregidgo, Ahmed K. Eldaly, Matteo Figini, Daniel C. Alexander
Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply.
2 code implementations • British Machine Vision Conference (BMVC) 2021 • Seunghoi Kim, Daniel C. Alexander
To overcome these problems, we propose a) a graph convolutional network (GCN) in an adversarial learning scheme where a discriminator network provides a segmentation network with informative information to improve segmentation accuracy and b) a graph convolution, GeoEdgeConv, as a means of local feature aggregation to improve segmentation accuracy and space and time complexities.
Ranked #6 on 3D Part Segmentation on ShapeNet-Part