I lead the Machine Learning Research team at the Toyota Research Institute (TRI) in Los Altos, CA, USA. My research focuses on scaling up ML for Robot Autonomy, spanning Scene and Behavior Understanding, Simulation for Deep Learning, 3D Computer Vision, and Self-Supervised Learning (cf. a short bio below). Outside of work, I spend time with my wife, daughter, and the mountains (I love camping, climbing, and snowboarding). You can find my publications, talks, and CV on this site. Enjoy!
- August 2020: we are organizing the ECCV 2020 workshop on Perception for Autonomous Driving (PAD)
- July 2020: we are organizing the ICML 2020 workshop on AI for Autonomous Driving (AIAD)
- July 2020: 2 papers (1 oral on trajectory prediction, 1 poster on differentiable rendering) accepted at ECCV 2020
- July 2020: 5 papers accepted at IROS 2020, and 1 at ITSC
- July 2020: 1 paper with Stanford on hierarchical RL and imitation in near-accidents accepted at RSS 2020
- June 2020: Together with colleagues from PFN and TRI-AD, we have released a survey on Differentiable Rendering.
- June 2020: 4 papers (3 orals!) accepted at CVPR 2020 (PackNet pseudo-lidar, real-time panoptic segmentation, auto-labeling, spatio-temporal graph distillation). See also our new DDAD dataset for depth estimation!
- February 2020: 1 paper with Stanford on Pedestrian Intent Prediction accepted at RA-L/ICRA 2020. See also our new STIP dataset!
- January 2020: I got promoted to Senior Manager! So grateful to my team and excited for our next steps together!
- December 2019: 1 paper accepted at ICLR 2020 and 1 (oral) at WACV 2020
- October 2019: 1 paper accepted at the International Journal of Computer Vision (IJCV)
- September 2019: 1 paper accepted at NeurIPS 2019 (also oral at BayLearn 2019) and 2 papers (spotlights) accepted at CoRL 2019
- July 2019: 1 paper accepted (oral) at ICCV 2019
- May 2019: I did an interview with the wonderful Sam Charrington for the TWIML AI podcast!
Adrien Gaidon is the Head of Machine Learning Research at the Toyota Research Institute (TRI) in Los Altos, CA, USA. Adrien’s research focuses on scaling up ML for robot autonomy, spanning Scene and Behavior Understanding, Simulation for Deep Learning, 3D Computer Vision, and Self-Supervised Learning. He received his PhD from Microsoft Research - Inria Paris in 2012, has over 40 publications and patents in ML/CV/AI (cf. Google Scholar), top entries in international Computer Vision competitions, multiple best reviewer awards, international press coverage for his work on Deep Learning with simulation, was a guest editor for the International Journal of Computer Vision, and co-organized multiple workshops on Autonomous Driving at CVPR/ECCV/ICML. You can find him at adriengaidon.com, on linkedin, and Twitter @adnothing.