works on

From the 1 of 61 linked papers with an AI index.

activity
20182025
most citedAutoNovel: Automatically Discovering and Learning Novel Visual Categories

151 citations · 284 across the 37 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cs.CV2019

Learning to Discover Novel Visual Categories via Deep Transfer Clustering

Kai Han, Andrea Vedaldi, Andrew Zisserman

We consider the problem of discovering novel object categories in an image collection. While these images are unlabelled, we also assume prior knowledge of related but different im…

cs.CV2019

Learning Transparent Object Matting

Guanying Chen, Kai Han, Kwan-Yee K. Wong

This paper addresses the problem of image matting for transparent objects. Existing approaches often require tedious capturing procedures and long processing time, which limit thei…

cs.CV2019

Semi-Supervised Learning with Scarce Annotations

Sylvestre-Alvise Rebuffi, Sebastien Ehrhardt, Kai Han +2

While semi-supervised learning (SSL) algorithms provide an efficient way to make use of both labelled and unlabelled data, they generally struggle when the number of annotated samp…

cs.CV2019

Unsupervised Image Matching and Object Discovery as Optimization

Huy V. Vo, Francis Bach, Minsu Cho +4

The paper reformulates unsupervised object category discovery and image matching as a formal optimization problem and demonstrates its effectiveness on benchmark datasets.

cs.CV20195 cited

Self-calibrating Deep Photometric Stereo Networks

Guanying Chen, Kai Han, Boxin Shi +2

This paper proposes an uncalibrated photometric stereo method for non-Lambertian scenes based on deep learning. Unlike previous approaches that heavily rely on assumptions of speci…