Is trajectory prediction promptable? Yes! Social-Transmotion, a generic Transformer-based model, makes it possible by integrating diverse visual cues as prompts. Joint work with Saeed, Yang, Kaouther. #ICLR2024
Paper: https://t.co/DghPRXAUBC
Webpage/code: https://t.co/wTG0LznuU4
🎉 Exciting news! Our team has achieved top rank on the nuScenes trajectory prediction leaderboard! Our strategy? Unprecedented data scaling with our new open-source framework .
Project page: https://t.co/rweCyE5s1M
Special thanks to Lan, hossein, kaouther, Eloi, & Matthieu!
Les véhicules neufs seront tous équipés d'un premier niveau d'assistance à la conduite en Suisse dès cette année. La @RadioTeleSuisse fait le point sur ce domaine d'innovation avec le prof. @AlexAlahi@EPFL. https://t.co/k3WzVSRXkX
🚗 #Débatsdété Pour ce 4e épisode, @AlexAlahi (@EPFL) passe en revue les avantages et les défis de l'#IA au service de l'automobile https://t.co/UXGRnR5TO2
Dear All, are you working in industry with AI/ML or know someone who does? You are dearly needed! It is time for another survey to threat model ML/AI in practice. Please take 10 minutes to click through our questions or share with someone who can help:
https://t.co/dXbeS92gWS
ChatGPT has shaken the world with its advancements in NLP. However, AI has still been found lacking in certain tasks, such as autonomous driving. Why? Click below to start the conversation:
https://t.co/hMOaaL1lxG
#AI#SelfDrivingCars#sociallyawareAI#tedx
Des scientifiques de l'ENAC collaborent avec @Dartfish et le @lausannehc pour repousser les limites de l’analyse vidéo sportive. Avec la contribution du prof. @AlexAlahi. L'objectif? La détection et le suivi automatisé des athlètes.
https://t.co/H2jUZG7NAK
Distribution shifts are grand challenges for machine learning models.
When it comes to motion, what are the unique problems and opportunities?
We provide an answer in our #CVPR2022 paper: “Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective”
1/6
"Vehicle trajectory prediction works but not everywhere"
#CVPR2022
Come and check our poster next week (June 24th morning, Session: Poster 4.1)
Project website and code: https://t.co/ZMLVI4ZnDk
Paper: https://t.co/kex77cCald
Joint work with @MHBahari@smoosavid@AlexAlahi
Thank you Andrej @karpathy (Director of AI at Tesla) for the great interactive Q&A during our “CIVIL 459: Deep Learning for Autonomous Vehicles" class. We all loved the interactions (including our robots!).
Do you want to generate photorealistic images?
We show that you can improve GAN-based methods by making their Discriminator semantically aware.
Code: https://t.co/kxvMarHOyt
Paper (ITS): https://t.co/SbzGSrj1NL
Project website: https://t.co/675bzfqGtO
At @EPFL_EN we believe Machine Learning is poised to fundamentally change the way we do Science and engineer solutions to our most pressing challenges.
If you’re a young researcher sharing this passion, apply to our new #AI4Science fellowship: https://t.co/hn1qqtINFn
Key takeaway
* both take-specific info (e.g. SSL) and model-specific info (e.g. feature moments) are crucial
* we should rethink what to store, in addition to model parameters, for robust deployment
Link: https://t.co/mn9Ll0QBdE
w/ Parth, Bastien, Baptiste, Taylor, @AlexAlahi
Test-time training (TTT) is an emerging approach to tackle distributional shifts. Yet, it's still not robust for practical use.
Have you ever wondered when TTT fails or thrives? Our paper TTT++ #NeurIPS2021 provides an answer.
To know more, plz join us at Session 1 this Tue :)
Stay informed on Imaging @EPFL_en : newsletter#2 is out. https://t.co/bz8B54jhFG
Don’t miss @AlexAlahi Lab presentation on his fascinating work on visual intelligence for transportation https://t.co/tQ68Elzmn1
Can we learn a robust motion representation (e.g., forecasting/navigation) from ill-distributed data?
Our #ICCV2021 paper 'Social-NCE' provides an answer!
(https://t.co/N31ooXp0dh)
Join us at Session 12 this Fri :)
w/ @qi_yan98, @AlexAlahi
https://t.co/u3wg5pYQ3J via @YouTube