rawalkhirodkar / egohumans Goto Github PK
View Code? Open in Web Editor NEW[ICCV, 2023] Multiple humans in 3D captured by dynamic and static cameras in 4K.
Home Page: https://rawalkhirodkar.github.io/egohumans/
License: Apache License 2.0
[ICCV, 2023] Multiple humans in 3D captured by dynamic and static cameras in 4K.
Home Page: https://rawalkhirodkar.github.io/egohumans/
License: Apache License 2.0
Small typo: cd ,,/mmhuman3d
should be cd ../mmhuman3d
.
Thanks for the great work!
Hi,
The supported benchmark Tracking in the README.md is invalid and there is no corresponding coco_track folder on the GoogleDrive.
I wonder if there will be a plan of releasing it so we can benchmark on the tracking, thank you!
Thank you for your work, it is inspiring and very interesting!
The link to supplementary material on ICCV open access is broken, I wonder if you can provide an alternative link to it! Thank you!
Hi Thanks for the great dataset. Following the instructions in VISUALIZE.md, I can successfully visualize the SMPL meshes on the fisheye ego views, e.g.
However, I wonder if there's a script to visualize them on the undistorted images, as in the video here?
Thanks for the reply.
-- Paul
Hi @rawalkhirodkar,
Thanks for releasing this dataset, this is very interesting and challenging for the research community.
In your paper you are not really mentioning the task of 3d human mesh recovery, do you plan (or do you already have something ready) for benchmarking human mesh recovery methods?
Should we use the same training/testing split as for the 2D pose benchmark? What do you think?
Thanks for you help and your time,
Best
Hello, thanks a lot for your interesting work. I have a question regarding the preprocessing you applied on aria images. Do you crop or rectify the images to compensate for radial distortions?
Hi, thank you for the great work!
I have a question about the dataset: are the intrinsic and extrinsic parameters of the stationary cameras provided? I didn't find them after downloading.
Thanks!
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