iRBSM: A Deep Implicit 3D Breast Shape Model

Maximilian Weiherer, Antonia von Riedheim, Vanessa Brébant, Bernhard Egger, Christoph Palm
12/17/2024
cs.CV

No official code found. Best implementation: mweiherer/irbsm (15 stars, MIT, last commit 2025-12-02).

Abstract

We present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-based predecessor, our model employs implicit neural representations; hence, it can be trained on raw 3D breast scans and eliminates the need for computationally demanding non-rigid registration -- a task that is particularly difficult for feature-less breast shapes. The resulting model, dubbed iRBSM, captures detailed surface geometry including fine structures such as nipples and belly buttons, is highly expressive, and outperforms the RBSM on different surface reconstruction tasks. Finally, leveraging the iRBSM, we present a prototype application to 3D reconstruct breast shapes from just a single image. Model and code publicly available at https://rbsm.re-mic.de/implicit.

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Code Implementations(1)

mweiherer/irbsmCommunity73%
MIT

Official implementation of "iRBSM: A Deep Implicit 3D Breast Shape Model" (BVM'25).

153PythonOct 16, 202410 months agoMIT

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Cite this paper

@article{weiherer2024irbsm,
  title  = {iRBSM: A Deep Implicit 3D Breast Shape Model},
  author = {Maximilian Weiherer and Antonia von Riedheim and Vanessa Brébant and Bernhard Egger and Christoph Palm},
  year   = {2024},
  eprint = {2412.13244},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.13244v1}
}

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