Learning To Count Objects in Images by Lempitsky, V, Zisserman, A

Deep image prior by Ulyanov, D, Vedaldi, A, Lempitsky, V

It takes (only) two: adversarial generator-encoder networks by Ulyanov, D, Vedaldi, A, Lempitsky, V

Deep image prior by Ulyanov, D, Vedaldi, A, Lempitsky, V

Symbiotic segmentation and part localization for fine-grained categorization by Chai, Y, Lempitsky, V, Zisserman, A

Counting in the wild by Arteta, C, Lempitsky, V, Zisserman, A

Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis by Ulyanov, D, Vedaldi, A, Lempitsky, V

A pylon model for semantic segmentation by Lempitsky, V, Vedaldi, A, Zisserman, A

Humanising GrabCut: Learning to segment humans using the Kinect by Gulshan, V, Lempitsky, V, Zisserman, A, IEEE

Texture networks: Feed-forward synthesis of textures and stylized images by Ulyanov, D, Lebedev, V, Vedaldi, A, Lempitsky, V

Detecting overlapping instances in microscopy images using extremal region trees by Arteta, C, Lempitsky, V, Noble, JA, Zisserman, A

Learning to detect partially overlapping instances by Arteta, C, Lempitsky, V, Noble, A, Zisserman, A

Learning to detect cells using non-overlapping extremal regions. by Arteta, C, Lempitsky, V, Noble, J, Zisserman, A

Interactive object counting by Arteta, C, Lempitsky, V, Noble, JA, Zisserman, A

Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics by Jones, FM, Arteta, C, Zisserman, A, Lempitsky, V, Lintott, CJ, Hart, T

Crystal nucleation in metallic alloys using x-ray radiography and machine learning by Liotti, E, Arteta, C, Zisserman, A, Lui, A, Lempitsky, V, Grant, P