Computer vision and AI

Stavros Tsogkas

So what is Computer Vision?

People don't just "see"

Goal: make sense of visual data

Semantic segmentation (Cityscapes dataset)

Fully convolutional neural networks

P(person)

P(horse)
:
P(dog)

dog

person

• Fully convolutional networks for semantic segmentation, Long et al., CVPR 2015.
• Semantic image segmentation with deep convolutional networks and fully-connected CRFs, Chen et al., ICLR 2015..

Part segmentation in images

Deep learning for semantic part segmentation with high-level guidance, Tsogkas et al., arxiv

Medical applications

Why automatic segmentation?

Putamen

Ventricle

Caudate

Amygdala

Hippocampus

Visualization and inspection

No need for manual annotation
(time consuming, need experts,
limited reproducibility)

Non-invasive diagnosis and treatment

Part segmentation in FMRI

Subcortical brain structure segmentation using FCNNs, Tsogkas et al., ISBI 2016

From 2D slices to 3D volumes

Our results

Groundtruth

More computer vision at UofT

• Object recognition (Sven Dickinson)
• Vision and language (Sanja Fidler)
• Computational photography (Kyros Kutulakos)
• Electron Cryomicroscopy (David Fleet)
• Semantic segmentation (Raquel Urtasun)

Visit my website:

http://www.cs.toronto.edu/~tsogkas/