Wayve
Wayve
  • Видео 144
  • Просмотров 378 425
CVPR24 E2EAI | Gianluca Corrado: Learning Models of the World
Learning Models of the World: Exploring Generative World Models in Autonomous Driving
Presented by Gianluca Corrado, Principal Scientist at Wayve. This session will focus on advancements in generative world models. Explore how integration of world models empowers autonomous vehicles to anticipate and strategize their actions, elevating safety and efficiency on the road. Discover how, by incorporating world models into driving algorithms, there exists the potential for enhanced comprehension of human decisions, ultimately facilitating better adaptability to a broader array of real-world situations.
More info: wayve.ai/cvpr-e2ead-tutorial/
Просмотров: 433

Видео

CVPR24 E2EAI | Nikhil Mohan: Towards Neural Simulator
Просмотров 40821 день назад
Towards Neural Simulator: Offline Validation of End-to-End Autonomous Driving Presented by Nikhil Mohan, Lead Scientist at Wayve, this session will focus on the development and application of neural simulators in autonomous driving. It will cover their roles in enhancing the validation and efficiency of end-to-end systems and their impact on advancing research in the domain. More info: wayve.ai...
CVPR24 E2EAI | Hongyang Li: Could Foundation Models really resolve End-to-end Autonomy?
Просмотров 61121 день назад
Presented by Hongyang Li, Principal Investigator at OpenDriveLab. This session will explore the evolution of autonomous driving from its early days to the current state-of-the-art technologies, focusing on the shift from modular to end-to-end approaches. More Info: wayve.ai/cvpr-e2ead-tutorial/
CVPR24 E2EAI | Jamie Shotton: Frontiers in End-to-End Learning for Autonomous Driving
Просмотров 89021 день назад
Presented by Jamie Shotton, Chief Scientist at Wayve. This segment delves into the latest advancements and methodologies in end-to-end learning tailored explicitly for autonomous driving, highlighting cutting-edge research and innovations in the field.
CVPR24 E2EAI | Long Chen: Introduction
Просмотров 87221 день назад
Presented by Long Chen, Staff Scientist at Wayve More info: wayve.ai/cvpr-e2ead-tutorial/
CVPR24 E2EAI | Oleg Sinavski: Language Meet Driving
Просмотров 36521 день назад
Language Meet Driving: Empowering End-to-End Autonomous Driving with Large Language Models (LLMs) Presented by Oleg Sinavski, Principal Scientist at Wayve. This session will focus on the usage of Large Visual-Language Models in autonomous driving. What are the benefits of adding language modality to a behaving autonomous robot? Here, we will cover topics in explainability, grounding textual mod...
CVPR24 E2EAI | Elahe Arani: Navigating the Future of End-to-End Autonomous Driving
Просмотров 37221 день назад
Navigating the Future of End-to-End Autonomous Driving: Reflections and Future Directions Presented by Elahe Arani, Head of AI Research at Wayve and Adjunct Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology. In the final session, we will reflect on the key insights gained throughout the tutorial, summarizing the fundamental concepts ...
PRISM 1 combined rgb depth
Просмотров 186Месяц назад
This section shows examples of scene reconstructions visualised alongside depth and 3D velocity magnitude rendered onto images. Note that these visualisations are reconstructions, not the real videos.
PRISM 1 combined aux vis
Просмотров 109Месяц назад
This section shows examples of scene reconstructions visualised alongside depth and 3D velocity magnitude rendered onto images. Note that these visualisations are reconstructions, not the real videos.
PRISM 1 London 4
Просмотров 150Месяц назад
PRISM-1, a scene reconstruction model of 4D scenes (3D in space time) from video data. Here we demonstrate PRISM-1’s capability to reconstruct a scene from various viewpoints by changing the camera path in two ways. When “freezing time” occurs, the ego-vehicle remains fixed in time while we pan the camera from left to right to view the scene from different angles. When the “freezing position” o...
PRISM 1 London 3
Просмотров 89Месяц назад
PRISM-1, a scene reconstruction model of 4D scenes (3D in space time) from video data. Here we demonstrate PRISM-1’s capability to reconstruct a scene from various viewpoints by changing the camera path in two ways. When “freezing time” occurs, the ego-vehicle remains fixed in time while we pan the camera from left to right to view the scene from different angles. When the “freezing position” o...
PRISM 1 Roundabout
Просмотров 68Месяц назад
PRISM-1, a scene reconstruction model of 4D scenes (3D in space time) from video data. Here we demonstrate PRISM-1’s capability to reconstruct a scene from various viewpoints by changing the camera path in two ways. When “freezing time” occurs, the ego-vehicle remains fixed in time while we pan the camera from left to right to view the scene from different angles. When the “freezing position” o...
PRISM 1 Road works
Просмотров 74Месяц назад
PRISM-1, a scene reconstruction model of 4D scenes (3D in space time) from video data. Here we demonstrate PRISM-1’s capability to reconstruct a scene from various viewpoints by changing the camera path in two ways. When “freezing time” occurs, the ego-vehicle remains fixed in time while we pan the camera from left to right to view the scene from different angles. When the “freezing position” o...
PRISM 1 Red light
Просмотров 70Месяц назад
PRISM-1, a scene reconstruction model of 4D scenes (3D in space time) from video data. Here we demonstrate PRISM-1’s capability to reconstruct a scene from various viewpoints by changing the camera path in two ways. When “freezing time” occurs, the ego-vehicle remains fixed in time while we pan the camera from left to right to view the scene from different angles. When the “freezing position” o...
PRISM 1 London 2
Просмотров 40Месяц назад
PRISM-1, a scene reconstruction model of 4D scenes (3D in space time) from video data. Here we demonstrate PRISM-1’s capability to reconstruct a scene from various viewpoints by changing the camera path in two ways. When “freezing time” occurs, the ego-vehicle remains fixed in time while we pan the camera from left to right to view the scene from different angles. When the “freezing position” o...
PRISM 1 Red Bus
Просмотров 54Месяц назад
PRISM 1 Red Bus
PRISM 1 London 1
Просмотров 48Месяц назад
PRISM 1 London 1
PRISM 1 Green Van
Просмотров 37Месяц назад
PRISM 1 Green Van
PRISM 1 Blue Car
Просмотров 32Месяц назад
PRISM 1 Blue Car
PRISM 1 Peds on crossing
Просмотров 53Месяц назад
PRISM 1 Peds on crossing
PRISM 1 Cyclist
Просмотров 51Месяц назад
PRISM 1 Cyclist
Riding The Wayve in the Countryside
Просмотров 311Месяц назад
Riding The Wayve in the Countryside
Ride The Wayve: Autonomous Driving in busy Central London
Просмотров 1,7 тыс.3 месяца назад
Ride The Wayve: Autonomous Driving in busy Central London
Wayve's AI Driver
Просмотров 6163 месяца назад
Wayve's AI Driver
Wayve LINGO-2 London Drive
Просмотров 3,7 тыс.3 месяца назад
Wayve LINGO-2 London Drive
Ride the Wayve: Uninterrupted autonomous driving
Просмотров 1,4 тыс.4 месяца назад
Ride the Wayve: Uninterrupted autonomous driving
Meet Wayve's new President, Erez Dagan
Просмотров 3515 месяцев назад
Meet Wayve's new President, Erez Dagan
Ride The Wayve with Christopher Young (Full video)
Просмотров 1,4 тыс.5 месяцев назад
Ride The Wayve with Christopher Young (Full video)
Ride The Wayve with Christopher Young
Просмотров 1965 месяцев назад
Ride The Wayve with Christopher Young
Ride The Wayve: Reacting to your Road
Просмотров 4706 месяцев назад
Ride The Wayve: Reacting to your Road

Комментарии

  • @JayCreates
    @JayCreates 11 дней назад

    Very nice indeed! to be honest you need to up the quality, of the video presentations on here.

  • @DanFrederiksen
    @DanFrederiksen 22 дня назад

    Good that you allow comments. I think you would benefit from higher quality cameras, not just resolution but tonal and color precision. The higher quality data should allow easier learning. Also can image synthesis ever hope to be high enough quality to be useful for training? it seems like it's a fruitless approach.

  • @toninocars
    @toninocars Месяц назад

    This actually can replace black cab drivers , we can still have the famous cabs but without grumpy Fella’s in who drives dodgy and had cockney accent

  • @MohamedSellamia
    @MohamedSellamia Месяц назад

    impressive!

  • @pary327
    @pary327 Месяц назад

    I wonder how long before Tesla drivers and investors start paying attention to this video. Elon, you have a problem. Btw they just gave the AI the UK highway code book as a pdf and just videos of other drivers. Wow, just wow.

  • @pary327
    @pary327 Месяц назад

    Impressive!

  • @rolandhanbury5641
    @rolandhanbury5641 Месяц назад

    This is certainly impressive. Once the Wayve car can meet another vehicle on a single track road, remember that it passed a passing place not too far back, and then reverse into it, then I really will bow down and say that AI is fully human equivalent, and better than most drivers.

  • @rolandhanbury5641
    @rolandhanbury5641 Месяц назад

    It blows my mind that if a video like this was put out by Tesla it would have hundreds of thousands of views and hundreds of comments, and yet here is a clearly superior technology and this is the first comment, 6 months after the video was released! I was beginning to lose faith that we would see self driving in wide availability in my lifetime (as I am quite old), but this video has restored my faith. I hope Wayve prospers even though capital is no longer easy to raise.

    • @pary327
      @pary327 Месяц назад

      I am quite heavily invested in Tesla stocks but I have to agree with you. The Wayve driving is natural. But with Tesla FSD videos every few minutes I am thinking, they need to work on that bit of the tech. Very impressed with Wayve.

  • @tryderrick
    @tryderrick Месяц назад

    Uber drivers soon finished.

  • @ryanf6530
    @ryanf6530 Месяц назад

    The neural net must be wondering where all the traffic lights are ;p

  • @WelcometoEuphoria
    @WelcometoEuphoria Месяц назад

    What does the car do in a situation in a single lane with passing places if neither vehicle can pass without one backing up? How is that negotiated with the oncoming vehicle? Or the one behind you?

  • @redemptionjack4657
    @redemptionjack4657 3 месяца назад

    Hm yeah nothing has changed Tesla does the exact same thing and once in mass used caused many deaths this is a shame learn no one wants a true self drivng car make auto pilot not this.

  • @changtimwu
    @changtimwu 8 месяцев назад

    Thank you. Just for curious, when regarding NeRF, is NVidia’s instant-ngp technology utilized in your work?

  • @jimj2683
    @jimj2683 9 месяцев назад

    You should release the driving simulator to the public as a game! It would be so fun to just drive around virtually and explore. It could replace Google Street View.

  • @BlakeEdwards333
    @BlakeEdwards333 10 месяцев назад

    What model architecture are you using here?

  • @alvarezbarbosa12
    @alvarezbarbosa12 10 месяцев назад

    Five years ago this company was already experimenting with end to end. Really fascinating to see.

  • @anthonyperez824
    @anthonyperez824 Год назад

    Your computer shows me nothing other than it doesn't give a shit about anyone on a bike and hate to tell you end to end mL isn't really new and it isn't the answer either Matter of fact that A lot of engineers stay far from it because it's a very unpredictable system and why the steering wheel all over the place

  • @yunusycle
    @yunusycle Год назад

    Very inspirational - great to see such visionaries marching towards the future!!

  • @CBikeLondon
    @CBikeLondon Год назад

    Thank you, please keep these coming, it's really excellent Wayve is London-based. Look forward to more content like this, as well as non-technical demos. So far those have been tightly controlled and cherry picked, it would be great to have much longer uncut videos.

  • @raidingshaman
    @raidingshaman Год назад

    Try testing in Bangladesh. Most AI cars will FAIL there

  • @jarosawsadowski6756
    @jarosawsadowski6756 2 года назад

    Saya tidak percaya ia boleh menjadi sebaik ini

  • @JazweenA221
    @JazweenA221 2 года назад

    Tesla is gonna be proud

  • @LarryBinFL
    @LarryBinFL 2 года назад

    Intuitively, this will ALMOST work....so long as you give the car a tremendous number of experiences. But I suspect it would kill a lot of people along the way, as it "learns" that sometimes the sun blinds it and sometimes people wearing camo are not landscape features, and, and, and......

  • @ChaseElliottBand
    @ChaseElliottBand 2 года назад

    This is how they do it with weaponized UAV, so it makes sense.

  • @rossfisher323
    @rossfisher323 2 года назад

    It's actually not the first example, OpenPilot has had End to End models since before then.

  • @nicholasdrivingacademy9435
    @nicholasdrivingacademy9435 2 года назад

    With the standard of some drivers bring on the self drive vehicles 🤖

  • @thebgEntertainment1
    @thebgEntertainment1 3 года назад

    seems like a similar approach to tesla/Openpilot, interesting

    • @Jayismynickname
      @Jayismynickname 3 года назад

      It is that’s why it’s the best approach to self driving

  • @my_master55
    @my_master55 3 года назад

    Soundtrack from the video: Frenchies - Moving Away 😁

  • @Trashbag-Sounds
    @Trashbag-Sounds 3 года назад

    the car drives mainly with semantic segmentation and depth. so the weather shouldn't matter as long as the segmentation works. what do i get wrong on this?

  • @Trashbag-Sounds
    @Trashbag-Sounds 3 года назад

    The depth map from a monocular view is amazing! Do you use a singel img or multiple imgs as input? motion would make the depth estimation much easyer

  • @Trashbag-Sounds
    @Trashbag-Sounds 3 года назад

    I hype your company so much 😅 for me as a stundet in ai .. this is like a dream! I would work for free for you. Just give me a call 😅😂

  • @Trashbag-Sounds
    @Trashbag-Sounds 3 года назад

    This is breathtaking. just amazing! the traffic light got me! just wow Where can I apply? ^^

  • @Trashbag-Sounds
    @Trashbag-Sounds 3 года назад

    this is just amazing! good job!

  • @dizapico
    @dizapico 3 года назад

    How I could contribute to this? I want try it on my Twizy

  • @DanFrederiksen
    @DanFrederiksen 3 года назад

    Maybe use a 4k camera for PR work instead of 95 webcam.

  • @mynewschannel3100
    @mynewschannel3100 3 года назад

    I wondered when you guys were going to move onto the Jaguar i-Pace :)

  • @hieuphan8335
    @hieuphan8335 4 года назад

    Hi, it's beautiful work. I have one question though. As the noise vector is sampled from the present distribution, how can you interpret the action name (e.g., turn left, right, straight) from the sampled vector? Let's say I want to "command" the model to imagine turn-left views. Is there any parameter that allows me to explicitly sample the "turning-left" vector from the present distribution?

    • @wayve
      @wayve 4 года назад

      Thanks! In this specific model that isn't possible, but if you condition the model on a navigation command like we did in arxiv.org/pdf/1912.00177.pdf, then you could achieve this

  • @RK-ve4xp
    @RK-ve4xp 4 года назад

    Amazing. I am afraid that self-driving cars will become more intelligent driver than most humans are with each passing year. They might even win in competitive car races in future like formula one.

  • @RK-ve4xp
    @RK-ve4xp 4 года назад

    Car is not confident enough to drive without jerking. Hopefully, it has learnt enough to become confident to drive straight and great. It is almost a year.

  • @yyl3683
    @yyl3683 4 года назад

    Amazing work

  • @SelfDrivingCarsNews
    @SelfDrivingCarsNews 4 года назад

    Great video guys! Keep working! Good luck!

  • @dLoLe
    @dLoLe 4 года назад

    Using asyncio, I see. People of culture.

  • @ugurkaraaslan9285
    @ugurkaraaslan9285 4 года назад

    What is different in your approach than Tesla in terms of reinforcement learning? Is small amount of RL training really enough to handle unforeseen exceptions? I am just curious not offensive. Thanks in advance. And congrats for your work.

  • @ugurkaraaslan9285
    @ugurkaraaslan9285 4 года назад

    Which RL algorithm is used? DQN, Actor- critic? Thanks in advance.

  • @ScienceAppliedForGood
    @ScienceAppliedForGood 4 года назад

    It's a very nice work done here. A way to go.

  • @calincanmircea664
    @calincanmircea664 4 года назад

    wow

  • @sushantgautam773
    @sushantgautam773 4 года назад

    Really Inspired from this work.

  • @mynewschannel3100
    @mynewschannel3100 4 года назад

    Glad to see you back, thought you had gone. How is your i Pace project going?

  • @matthewfelgate
    @matthewfelgate 4 года назад

    Have you got any videos of your self-driving cars interacting on the road with other cars? When will you do a passenger test service?

  • @LCUGUEN
    @LCUGUEN 4 года назад

    Your team make an amazing job👌