Vlad Paunescu
76 posts


I'm @ChessvisionAi a Twitter bot to help you analyze chess diagrams. To trigger me, reply to any tweet with a chess diagram and mention me with the "scan" keyword and I'll reply back with my analysis. You can also use keywords "scan white" or "scan black" to hint whose turn is it

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Vlad Paunescu retweetledi
Vlad Paunescu retweetledi

Extending #StyleGAN3's GUI, part 1: added the rest of the affine transformations: scale, shear, and mirror in both horizontal and vertical axes. Here I showcase with FFHQU-256, config-r, so that I have a higher FPS (cc @hexorcismos). Updated GUI found at: github.com/PDillis/styleg…
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Vlad Paunescu retweetledi
Vlad Paunescu retweetledi
Vlad Paunescu retweetledi

@raoult_didier Hello! Have you tried using Azithromycin alone because of Hydroxychloroquine side effects?
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Notre étude porte sur 80 patients, sans groupe contrôle car nous proposons notre protocole à tous les patients ne présentant pas de contre-indication.
C'est ce que nous dicte le serment d'Hippocrate que nous avons prêté.
mediterranee-infection.com/epidemie-a-cor…
Didier Raoult@raoult_didier
Nouveaux résultats de l'IHU Méditerranée Infection : 80 patients traités par une association hydroxychloroquine/azithromycine. mediterranee-infection.com/wp-content/upl…
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Vlad Paunescu retweetledi
Vlad Paunescu retweetledi

We've trained an AI system to solve the Rubik's Cube with a human-like robot hand.
This is an unprecedented level of dexterity for a robot, and is hard even for humans to do.
The system trains in an imperfect simulation and quickly adapts to reality: openai.com/blog/solving-r…
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Vlad Paunescu retweetledi
Vlad Paunescu retweetledi

Reconstructing scene depth from video with moving subjects can be very challenging. Now there’s a #DeepLearning approach that generates accurate 3D depth maps from ordinary video, even when both camera and subjects are in motion. Learn more at → goo.gle/2HxYqCm
GIF
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Vlad Paunescu retweetledi

@UCBerkeley DeepDrive and DiDi are co-hosting two challenges in #CVPR2019 Workshop on Autonomous Driving. The challenges will focus on domain adaptation of object detection and tracking based on datasets from BDD and DiDi. Register now! bair.berkeley.edu/blog/2019/03/2…

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Vlad Paunescu retweetledi

Stroke of Genius: GauGAN Turns Doodles into Stunning, Photorealistic Landscapes blogs.nvidia.com/blog/2019/03/1…
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Vlad Paunescu retweetledi

Learning Correspondence from the Cycle-Consistency of Time. New work from CMU/Berkeley shows how cycle-consistency can help a large number of diverse correspondence problems in vision! arxiv.org/abs/1903.07593 #computervision #cvpr2019

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Vlad Paunescu retweetledi

Our #CVPR2019 solves video object segmentation end-to-end with a NN: a ConvLSTM both discovers objects in the video frames dimensions, and tracks them across time.
Joint effort by @UOCuniversitat @BSC_CNS & @la_UPC. #DLUPC
Project page: imatge-upc.github.io/rvos/
Carles Ventura@carles_ventura
Our paper "RVOS: End-to-End Recurrent Network for Video Object Segmentation" accepted at CVPR2019 and done in collaboration with BSC (@miriambellver) and UPC (@Grouco, @amaiasalvador, Ferran Marques and @DocXavi) is already available in arXiv: arxiv.org/abs/1903.05612 #cvpr2019
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Vlad Paunescu retweetledi

It turns out that only a few parameters need to be trained to fine-tune huge text transformer models. Our latest paper is on arXiv; work @GoogleAI Zürich and Kirkland. bit.ly/2DXCgb7 #GoogleZurich #GoogleKirkland

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