CVPR 24: Language models in end-to-end autonomous driving
Check out other great talks from the E2E Autonomoy Tutorials session.
- Why use Language models in end-2-end driving?
- Measuring LLM capabilities in driving
- Paper survey: Non-visual LLMs in self-driving
- Paper survey: VLMs for perception in self-driving
- Why is it important to go end-2-end with VLMs?
- Paper survey: End-2-end VLMs in self-driving
- Unsolved problems, conclusions, Q&A
BMVA 2024: Trustworthy Multimodal Learning with Foundation Models
Talk at a Trustworthy Multimodal Learning with Foundation Models meeting
- Why use Language models in end-2-end driving?
- Lingo-1
- LingoQA and a trainable LLM judge
- Trustworthiness and explainability of end-2-end models
- Lingo-2
WandB Fully Connected: Vision language action models for autonomous driving at Wayve
This is a short version of the BMVA 2024 talk above at the WandB event.
WACV 2024: Large language and Vision models for Autonomous driving
Keynote talk at LLVM-AD workshop
- Software 2.0, Wayve’s end-2-end approach
- Lingo, LingoQA
- GAIA-1
Language and Video generative AI in Autonomous Driving
Chalmers University of Technology, guest lecture for SSY340 – Deep Machine Learning course
- Autonomous driving introduction and previous systems
- Software 2.0, Wayve’s end-2-end approach
- Limitations of end-2-end systems
- Lingo-1
- GAIA-1
Sensory Fusion for Scalable Indoor Navigation
2019 Embedded Vision Summit. Slides.
An older presentation about perception system of BrainCorp robots.