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20182021
most citedLearning Representations of Sets through Optimized Permutations

8 citations · 25 across the 8 of their papers we have counts for

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cs.CV2021

Language Models as Zero-shot Visual Semantic Learners

Yue Jiao, Jonathon Hare, Adam Prügel-Bennett

Visual Semantic Embedding (VSE) models, which map images into a rich semantic embedding space, have been a milestone in object recognition and zero-shot learning. Current approache…

cs.CV2021

What Remains of Visual Semantic Embeddings

Yue Jiao, Jonathon Hare, Adam Prügel-Bennett

Zero shot learning (ZSL) has seen a surge in interest over the decade for its tight links with the mechanism making young children recognize novel objects. Although different parad…

cs.CV20215 cited

Learning to Draw: Emergent Communication through Sketching

Daniela Mihai, Jonathon Hare

Evidence that visual communication preceded written language and provided a basis for it goes back to prehistory, in forms such as cave and rock paintings depicting traces of our d…

cs.CV2021

Differentiable Drawing and Sketching

Daniela Mihai, Jonathon Hare

We present a bottom-up differentiable relaxation of the process of drawing points, lines and curves into a pixel raster. Our approach arises from the observation that rasterising a…

cs.CV20211 cited

The emergence of visual semantics through communication games

Daniela Mihai, Jonathon Hare

The emergence of communication systems between agents which learn to play referential signalling games with realistic images has attracted a lot of attention recently. The majority…

cs.CV20201 cited

How Convolutional Neural Network Architecture Biases Learned Opponency and Colour Tuning

Ethan Harris, Daniela Mihai, Jonathon Hare

Recent work suggests that changing Convolutional Neural Network (CNN) architecture by introducing a bottleneck in the second layer can yield changes in learned function. To underst…