mlsanityData to 7 Oct 2026

APES: Articulated Part Extraction from Sprite Sheets

arXiv 2206.02015 ↗First posted 4 Jun 2022cs.CV cs.GRcited by 0

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Abstract (arXiv)

Rigged puppets are one of the most prevalent representations to create 2D character animations. Creating these puppets requires partitioning characters into independently moving parts. In this work, we present a method to automatically identify such articulated parts from a small set of character poses shown in a sprite sheet, which is an illustration of the character that artists often draw before puppet creation. Our method is trained to infer articulated parts, e.g. head, torso and limbs, that can be re-assembled to best reconstruct the given poses. Our results demonstrate significantly better performance than alternatives qualitatively and quantitatively.Our project page https://zhan-xu.github.io/parts/ includes our code and data.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 29 of its 62 references that are in the map. First posted on arXiv 4 Jun 2022.

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29 of 62 references.

References · 29

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17 more
  1. 2020Interior Point Solving for LP-based prediction+optimisationcited by 83
  2. 2020Continuous Surface Embeddingscited by 79
  3. 2018Deep Part Induction from Articulated Object Pairscited by 66
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  8. 2021MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronizationcited by 46
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  17. 2019Neural Puppet: Generative Layered Cartoon Characterscited by 7

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