Відео

thanks so much for having this stuff up. Watching through your videos and its super useful!

very glad to see how the author explain details and process of HRnet,thanks to this video

Great video, can we get more explanation regarding the mathematical part on each paper, wolud love it if you do so.

When VQA will be ready to use? Anytime soon?

More lectures like this based on computer vision concepts please!🔥

Great work, great presentation!

This was a perfect intro to BlenderProc. Thanks Maximilian for making such an awesome tool opensource and Peter for organising this session !

Thanks for u sharing

Thanks for your sharing. This is a great tutorial! I am Yanyi Zhang from Dalian University of Technology, China. I read your work recently and wanna explore this field in the future.

How can I get the results of this work?

Hi can you suggest me some pipeline for generating keypoint synthetic datasets using blender ?

What was the quality of the camera images and lidar points?

What kind of tools were used for annotation of camera and lidar data?

I love how peter also asks about the thought process of the author on how he came up with the ideas. Gem !

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I'm just curious if the reconstructed geometry provide information such as for example, the volum of the backrest? or the width, height and length of it? would be great to hear back an answer

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We have recently read about your work and want to study this topic in a more challenge open world setting. Much happy to see your videos here. Love from Northwestern Polytechnical University, China.

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Nice work

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Hey Peter, nice video, wondering why in the 3d to 3d decoder, you did classification of point cloud instead of using a CNN and comparing the output voxel with bceloss for example? thanks in advanced for the answer.

great work, Thanks for hosting this

Hello, thank you for your video. It's clear and instructive. I am wondering about the color. Does the model keep the original picture color ? Can the 3D model has color, and for the unreveal part of the model can it guess the color ? How that it works ? Do you have resources to share with me ?

Very good. Thank you!

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... could you talk about artificial neural network with output layer binarized...?

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Great talk and this did not hit my research radar, helped me catch up with the state-of-the-art in this topic. I am trying to find the repo which is 404 given in the paper. It would be great if the authors can make their repo public to reproduce their results.

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Your Recording is awesome which helped to gain basic knowledge related to the project which is similar to the idea concept. The project is based on 3D reconstruction using 2 or 3 orthographic views(engineering drawings) please suggest to me how to get the solution.

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