At #CVPR2024: we present pix2gestalt, which synthesizes whole objects from occluded ones, enabling zero-shot amodal segmentation, recognition, and 3D reconstruction!
Project Page: https://t.co/mjvjuEdfYM
Code: https://t.co/0i7sEXsg7x
arXiv: https://t.co/LxJfvtwXio
📢 Releasing TRI's open-source Mamba-7B trained on 1.2T tokens of RefinedWeb!
Mamba-7B is the largest fully recurrent Mamba model trained and is a state-of-the-art recurrent LLM. 🚀🚀🚀
https://t.co/PmsoRc4SNG
#VCAD@CVPR is successfully concluded! We sincerely thank speakers and audiences for coming and those fruitful discussions of the future of vision-centric and data-driven driving. Here are some pictures we took at the venue: https://t.co/HM1nLfwVng (credits @xinhaoliu16)
In case you are exploring the agenda on June 19th (Monday) for #CVPR2023 , we are organizing the full-day Vision Centric Autonomous Driving Workshop (VCAD)! Come and join us for wonderful talks and challenges! More details here: https://t.co/iFNliqe3z1
In case you are exploring the agenda on June 19th (Monday) for #CVPR2023 , we are organizing the full-day Vision Centric Autonomous Driving Workshop (VCAD)! Come and join us for wonderful talks and challenges! More details here: https://t.co/iFNliqe3z1
Come to our poster 30a at Tuesday morning’s 10:00am - 12:30pm session; we'd love to chat with you about how we made SoTA test-time adaptation with self-supervised contrastive learning! #CVPR2022#UCBerkeley@DequanWang@trevordarrell@SaynaEbrahimi
https://t.co/AoB9J18Tta
Inferring depth from cameras can help save lives, increase mobility, reduce costs, and improve manufacturing processes.
In our latest blog, TRI's machine learning team takes it one step further and shows how to bring #monodepth to the real world ⬇️ https://t.co/Wxe4VhQ6N5
Checkout our work AdaContrast accepted to #CVPR2022 that achieves SoTA performance on test-time adaptation! Code is available. Shout-out to my wonderful collaborators @UCBerkeley: @DequanWang, @trevordarrell and @SaynaEbrahimi!
https://t.co/AoB9J0Ri4A
Checkout our work AdaContrast accepted to #CVPR2022 that achieves SoTA performance on test-time adaptation! Code is available. Shout-out to my wonderful collaborators @UCBerkeley: @DequanWang, @trevordarrell and @SaynaEbrahimi!
https://t.co/AoB9J0Ri4A