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Thomas Joy

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3

identity via Semantic Scholar / OpenAlex

most citedReal-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC

16 citations · 16 across the 1 of their papers we have counts for

collaborators

3 papers

cs.CV2019★ 16 cited

Real-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC

Oscar Rahnama, Tommaso Cavallari, Stuart Golodetz +5

Obtaining highly accurate depth from stereo images in real time has many applications across computer vision and robotics, but in some contexts, upper bounds on power consumption c…

cs.CV2019

Learning to Adapt for Stereo

Alessio Tonioni, Oscar Rahnama, Thomas Joy +3

Real world applications of stereo depth estimation require models that are robust to dynamic variations in the environment. Even though deep learning based stereo methods are succe…

cs.CV2018

Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials

Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan +5

Dense conditional random fields (CRFs) have become a popular framework for modelling several problems in computer vision such as stereo correspondence and multi-class semantic segm…

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