activity
20152023
most citedAutoNovel: Automatically Discovering and Learning Novel Visual Categories

151 citations · 561 across the 38 of their papers we have counts for

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Showing 2017Show all

5 papers · 1 filter

cs.CV201715 cited

DeepRadiologyNet: Radiologist Level Pathology Detection in CT Head Images

Jameson Merkow, Robert Lufkin, Kim Nguyen +3

We describe a system to automatically filter clinically significant findings from computerized tomography (CT) head scans, operating at performance levels exceeding that of practic…

cs.CV20178 cited

Learning to Represent Mechanics via Long-term Extrapolation and Interpolation

Sébastien Ehrhardt, Aron Monszpart, Andrea Vedaldi +1

While the basic laws of Newtonian mechanics are well understood, explaining a physical scenario still requires manually modeling the problem with suitable equations and associated…

cs.CV201712 cited

Unsupervised learning of object frames by dense equivariant image labelling

James Thewlis, Hakan Bilen, Andrea Vedaldi

One of the key challenges of visual perception is to extract abstract models of 3D objects and object categories from visual measurements, which are affected by complex nuisance fa…

cs.CV2017

Learning multiple visual domains with residual adapters

Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi

There is a growing interest in learning data representations that work well for many different types of problems and data. In this paper, we look in particular at the task of learn…

cs.AI201738 cited

Learning A Physical Long-term Predictor

Sebastien Ehrhardt, Aron Monszpart, Niloy J. Mitra +1

Evolution has resulted in highly developed abilities in many natural intelligences to quickly and accurately predict mechanical phenomena. Humans have successfully developed laws o…