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# [CVPR 2021] Mesh Transformer 논문 리뷰 - 정완이의 개발 일기장
METRO: End-to-End Human Pose and Mesh Reconstruction with Transformers
[https://on-jungwoan.github.io/dl_paper/metro/](https://on-jungwoan.github.i…
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Congratulations on your paper being accepted! I've been following your work since January this year. I believe real-time human reconstruction is very meaningful, and I hope to conduct research based o…
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Hi, this is an amazing work that combines understanding and generation into one single tokenizer. Have you guys tried lower bandwidth, e.g. less than 20 or even 15 tokens per second?
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Hello! Thank you for your excellent work. I would like to ask how to run the data collected by myself on human performers and extract those human surfaces. Specifically, I want to know how to prepare …
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Hi,
Appreciate the nice code release! Could you also share the videos for the datasets gymnastics, NBA? That would be really helpful for testing other human mesh reconstruction approaches. Thanks!
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Hi, thanks for your great work and model, I want talking about the reconstruction quality of released TiTok.
I found the reconstruction visualization is not good, see the following picture. In the ar…
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Hello, many thanks for your code sharing.
I'm now trying to reproduce the training process on BEHAVE (download from official website). I keep the same settings as the initial code. However, the final…
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Hello and thank you for your work.
I am trying to run your method in a custom dataset and I am trying to see what is the minimum data requirements. Given a dataset structurally similar to ZJU-MoCap…
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Hi @krennic999
Thank you for your excellent work!
I am very interested in the high-quality and detailed human face images you demonstrated in your paper, like the ones below:
In this [iss…
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https://www.biorxiv.org/content/early/2018/02/27/272518
TMats updated
6 years ago