TrimBot2020

The big Trimbot group

TrimBot2020 mentioned on Horizon: the EU Research & Innovation magazine

The TrimBot2020 project was mentioned in an article on Horizon: the EU Research & Innovation magazine. Here an extract of the article, which you can read here. “It’s a similar story for the robotic hedge trimmer being developed by a separate group of researchers. All the farmer or groundskeeper needs to do is mark which hedge needs trimming. ‘The user will sketch the garden, though not too accurately,’ said Bob Fisher, computer vision scientist at Edinburgh University, UK, and coordinator…

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FlowNet 2.0 @CVPR 2017

FlowNet 2.0 is the first optical flow approach based on deep learning that reaches state-of-the-art accuracy. At the same time it is by a factor 100 faster than previous state-of-the-art techniques. This allows for reliable motion estimation at interactive frame rates. For more information visit the paper page.

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DeMoN @CVPR 2017

DeMoN is the very first work that formulates the problem of joint egomotion and depth estimation as a pure learning problem. Given two images from a single moving camera, DeMoN can estimate depth and camera motion at interactive frame rates. For more information, please visit the website.

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Twitter
Check out the new #paper by the team at @EdinburghUni on "3D plane labeling #stereo #matching" https://t.co/PvatuaAjko #3dvision @EU_H20202 weeks
A new #contribution to the project from @EdinburghUni team. Check it out https://t.co/cqjQwtfUNw #robotics #vision @EU_H2020 @EUScienceInnov3 weeks
#GroundTruth recording in the #garden at @WUR. Stay tuned for the #dataset releases :) #3d #reconstruction #vision https://t.co/7uyOXpCDy44 weeks
RT @EU_H2020: #FF #H2020 @CARISMAND @InVID_EU @iMETland @RADARCNS @RESCEUproject @PAL4Uproject @BAMB2020 @AdaptSmartIMI @sparks_eu…4 weeks
"Embedded Real-time Multi-Baseline Stereo" #contribution at #ICRA17 by our partners @ETH_en https://t.co/1nIkJYxXX44 weeks