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UNetXST | Camera to Bird's Eye View | Perception for Self Driving Cars
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- Опубликовано: 17 авг 2024
- Discussing a technique to convert images taken from different self driving cameras to a bird's eye view or top level view representation. The network makes use of a combination of UNet and Spatial Transformers.
Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements.
Twitter: / mahnasakshay
LinkedIn: / sakshaymahna
Links
Dataset: www.kaggle.com...
Dataset Visualization: www.kaggle.com...
Notebook/Code: www.kaggle.com...
UNetXST Paper: arxiv.org/pdf/...
UNetXST Github Repository: github.com/ika...
UNet: towardsdatasci...
Image Transformations: kevinzakka.git...
Spatial Transformer Networks: kevinzakka.git...
Videos on Image Segmentation
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Multi Task Attention Network: • Multi Task Attention N...
Fully Convolutional Network: • Fully Convolutional Ne...
Wow!! Great video! Thank you for your time and clear explanation. Cheers!
Awesome, thanks!
Great information 👍
I am figuring out how the same can be done using self-supervised method so that it can be applied to a different set of images for which bev labels are not available.
But why we can use semnatlcly
Is there any limit to the number of cameras?
I would say no
Please do path planning from a bird's eye view including explanation of algorithms.
Thank you! Really nice suggestion, I'll look into it!
Hello! You can checkout the latest video. Link: ruclips.net/video/nbaSzCnmyec/видео.html
Hope you like it.
Why has nobody collected data from the real world? You could attach a pole with a downward-facing camera on top of a bunch of teslas and drive around collecting data. Then you have all the ground truth you need for making 360 parking cameras much better.
Hey Sakshay! Great video. I've sent you a mail. Would you please have a look at it! 😉
Hello Pranshu! Yes, I'll have a look.