N-gated Hacker NewsMay 19
🎨🤖 Behold! The latest revolution in artistic laziness—SetPose, the free 3D pose maker that turns the epic struggle of drawing into a game of shortcut twister! With more instructions than a NASA launch sequence, this tool is perfect for anyone who thinks 'Ctrl + Z' is the true art form. 🎨🔄
https://setpose.com/ #artisticlaziness #3Dpose #creativehacks #digitalart #techinnovation #HackerNews #ngated
SetPose: Free 3D Pose Maker — Mannequin Drawing Poses - SetPose.com

The easy to use pose maker for artists! Adjust the 3D drawing model to create your own custom poses. Combine them with many props to use as a drawing reference

Urs WaldmannOct 19, 2023

We launched our project page for 3D-MuPPET https://alexhang212.github.io/3D-MuPPET/.

A framework to estimate and track 3D poses of up to 10 #pigeons at interactive speed. We show that 3D-MuPPET also works in natural environments without model fine-tuning on additional annotations.

#MuPPET
#PoseEstimation
#3dpose
#tracking
#computervision
#collectivebehaviour
#UniKonstanz
#CBehav
#cv4animals

3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking

Project page for '3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking'

Show threadkari hoffmanAug 2, 2023
@lili congrats and good luck! I am shamelessly self serving when I say that I hope you have great success with the #3Dpose estimation work. Especially if it can generalize to #monkey!
Urs WaldmannMar 3, 2023

Our latest work "Neural Puppeteer" is published at https://link.springer.com/chapter/10.1007/978-3-031-26316-3_15.

We estimate 3D keypoints from multi-view silhouettes only, using our inverse neural rendering pipeline. In this way our 3D keypoint estimation is robust against transformations that leave silhouettes unchanged like texture and lighting.

#NePu #NeuralRendering #PoseEstimation #3dpose #computervision #CBehav #UniKonstanz

Neural Puppeteer: Keypoint-Based Neural Rendering of Dynamic Shapes

We introduce Neural Puppeteer, an efficient neural rendering pipeline for articulated shapes. By inverse rendering, we can predict 3D keypoints from multi-view 2D silhouettes alone, without requiring texture information. Furthermore, we can easily predict 3D...

SpringerLink