@metro_madrid un metro cada 9 min el finde en la línea 5, porque tan pocos? Apretados como sardinas todo el trayecto con dos niñas, intentamos usar transporte público al máximo pero la próxima será con coche :-(
I wanted to see how the latest stereo approaches perform in the wild with my @luxonis OAK-D Lite camera, so I made stereodemo. It compares 4 deep learning methods + OpenCV baselines on files or OAK-D streams. Just one "pip install" away: https://t.co/4cO4ONoj0Q
@LaFranceOSi Bonjour, y'aura-t-il bientôt un nouveau formulaire sur votre site ? Le formulaire sur https://t.co/bkB4d7OJWo est toujours pour le troisième trimestre 2022/23.
We launche a petition to democratize AI research by establishing an international, publicly funded supercomputing facility equipped with 100,000 state-of-the-art AI accelerators to train open source foundation models.
https://t.co/jbkQnlEHYH
https://t.co/agmh1Ptjky
Thrilled to shared that I was awarded with the #GTRob award for the best thesis in robotics in Spain! Thanks to #UniZar for having the opportunity to work and learn from some of the best SLAM researchers. Now let's keep working on real SLAM, new exciting times in @arcturusvision
Releasing 🌟nerfstudio🌟, a plug-and-play python library to easily create your own NeRFs!
@nerfstudioteam is a contributor friendly open-source repo with a realtime web viewer that makes it easy to make cool videos 📽️
https://t.co/zw0ZPqIZ4c
https://t.co/NZM8GPjNrF #nerfstudio 1/
Having great fun with @ElevenVR , feels very realistic! It's also interesting how you can get hints about the personality of other players even without video nor audio, just from corporal language playing table tennis.
@grbradsk@luxonis Yes indeed I did some speed/memory comparison, and while I didn't try to run any of them on device, I'm quite hopeful for several of them once optimized and configured with a speed-oriented trade-off. Would be very cool to see!
@luxonis Just added DistDepth (CVPR 2022) https://t.co/UwLbkx0SAs . It is a monocular method and thus only uses the left image, but still interesting to see how it compares to the stereo methods. `pip install --upgrade stereodemo` to try it.
@luxonis Wrote a small blog post comparing these algorithms more in depth, with speed/memory measurements and longer comparison videos: https://t.co/tWnyTQHUBJ
Overall the latest deep learning results are pretty impressive on things like blank walls, even if they were not trained on that. In particular I found RAFT-Stereo (3DV 2021) to have a nice perf/quality tradeoff with its real-time settings.