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[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

Python 96.02% Shell 3.98%
egocentric-vision human-pose-estimation mesh multiview-learning structure-from-motion

egohumans's Introduction

Hi there ๐Ÿ‘‹

[Rawal's GitHub stats

egohumans's People

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egohumans's Issues

Missing tracking benchmark files

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!

Supplementary Materials of the Paper

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!

Visualizing pose3d or smpl meshes on undistorted ego images

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.
image
However, I wonder if there's a script to visualize them on the undistorted images, as in the video here?
image

Thanks for the reply.

-- Paul

Benchmark for evaluating human mesh recovery

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

preprocessing

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?

Parameters of stationary cameras

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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