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Generating a 3D Human Pose & Shape from a Single Image E9

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Archived series ("Inactive feed" status)

When? This feed was archived on June 27, 2017 21:12 (7y ago). Last successful fetch was on May 28, 2017 17:01 (7y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

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Manage episode 172178735 series 1373620
Content provided by Chad Wittman. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Chad Wittman or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
When a human sees another human, they possess a wealth of information on how that body might exist within our physical world. When a machine sees a human in the same pose, the machine does not understand the pose and it’s implications. For example, the machine doesn’t know that my elbow bends inwards instead of outwards. For future robots interacting with humans, especially any robots that would be physically touching a human — it would be incredibly important for it to understand the ways in which I can and cannot bend. This episode we speak with Christoph Lassner who worked on extracting a 3D model of a human pose & shape based on a single photo. We’ll show a few examples of what this looks like and how it works in the show. Details: http://www.creativeai.net/posts/v8w2WYnQaahwcsbfs/smplify-3d-human-pose-and-shape-from-a-single-image Follow the podcast: http://ai-guild.com Want to see more Creative AI research? http://www.creativeai.net Are you a Machine Learning Engineer looking for a new job? Machine Learning Jobs by Amazon: http://jobs.ai-guild.com
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11 episodes

Artwork
iconShare
 

Archived series ("Inactive feed" status)

When? This feed was archived on June 27, 2017 21:12 (7y ago). Last successful fetch was on May 28, 2017 17:01 (7y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 172178735 series 1373620
Content provided by Chad Wittman. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Chad Wittman or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
When a human sees another human, they possess a wealth of information on how that body might exist within our physical world. When a machine sees a human in the same pose, the machine does not understand the pose and it’s implications. For example, the machine doesn’t know that my elbow bends inwards instead of outwards. For future robots interacting with humans, especially any robots that would be physically touching a human — it would be incredibly important for it to understand the ways in which I can and cannot bend. This episode we speak with Christoph Lassner who worked on extracting a 3D model of a human pose & shape based on a single photo. We’ll show a few examples of what this looks like and how it works in the show. Details: http://www.creativeai.net/posts/v8w2WYnQaahwcsbfs/smplify-3d-human-pose-and-shape-from-a-single-image Follow the podcast: http://ai-guild.com Want to see more Creative AI research? http://www.creativeai.net Are you a Machine Learning Engineer looking for a new job? Machine Learning Jobs by Amazon: http://jobs.ai-guild.com
  continue reading

11 episodes

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