3D-Net: Monocular 3D object recognition for traffic monitoring
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- Опубліковано 14 лис 2024
- Finally, our extensive research for 3D vehicle/pedestrian detection and interactions is out + the SOURCE CODE (provided on 02/05/2023)!
We expect a high level of interest, especially from the #ComputerVision, #DNN, #VehicleAutomation, and #ITS research community. Open Access Article: www.sciencedir...
Source code: codeocean.com/...
Thanks to my amazing co-authors Mohsen Azarmi and Farzam Mohammad Pour for their great contributions.
#MachineLearnig #AI #TrafficManagement #RoadSafety
#Research #Transportion #AutonomousVehicles
Congratulation! I have looking for it for a long time!
Hope you like it!
We are pleased to let you know that the source code is just shared! Please revisit.
This project is fabulous.hope you win top conference!
Thank you!
We are pleased to let you know that the source code is just shared! Please revisit. We also published our work in Elsevier journal of Expert Systems with Applications (Impact Factor: ~ 9.0)
Great Job, congrats on the new paper.
Thank you!
We are pleased to let you know that the source code is just shared! Please revisit.
Hi Mahdi, this is really awesome demo. May I post this on my social media with credit to you ofcourse?
Given that you intent to provide credit and reference, it would be fine.
I've been following this project for a long time, and I'm not sure when the creator will release a detailed tutorial.
Please see the video description. It is now 7 months that we have published the code. See the video description :)
good job，your works in Chinese vedio is more than 10000 hits
Thank you!
We are pleased to let you know that the source code is now shared! Please revisit.
Great, how do you map the prespective view to a bird view, in other words, how do you translate the x,y pixel to the world coordination?
Please refer to the our pre-print and the given references for BEV mapping.
We are pleased to let you know that the source code is just shared! Please revisit.
Sir, could you please provide the code for training the model (where you trained the model on the dataset)?
The details are provided in the paper + code.
Wow its great project. Amazing
Thank you! Cheers!
We are pleased to let you know that the source code is now shared! Please revisit.
I'm very interested in this work. Is it possible to apply it to a custom dataset? I guess the answer is yes, but it might take a lot of work.
Yes, please refer to the published paper and code
Your project is really awsome! Can you please share the code?
Good news. The code is shared now! Please revisit.
Do I need a pretrained model for 3d boxes or can I use transfer learning or better running 3d box algorithm instead on 2d BB trained model?
The code is shared now! You may have a look
We are pleased to let you know that the source code is just shared! Please revisit.
Hello Mr. Rezaei, I tried to connect with you by mail, I hope to hear from you regarding my queries
Just found your email in my spam folder. I am afraid but we do not work on parking lots monitoring and have no time to investigate if further for you. You may better to contact someone who directly works in that area.
how many fps do you process? i believe you dont need 60 fps or even 30 fps for traffic monitoring
We process 30 fps. Thanks for asking
Could you pls share the code?
The code can not be released at this stage due to commercialisation of the project.
We are please to let you know that the source code is shared now! Please revisit.
Hi,
May i ask share MIO-TCD dataset,
Because original link disappered.
and only small part of MIO-TCD dataset available on kaggle.
Thanks
Hi. Thanks for your comment, but only the owners of the MIO-TCD dataset should share it. We can not and should not re-share the dataset of others. It is their responsibility to fix their web-link.