3DIAS: 3D Shape Reconstruction with Implicit Algebraic Surfaces


3D Shape representation has substantial effects on 3D shape reconstruction. Primitive-based representations approximate 3D shape mainly by a set of simple implicit primitives, but the low flexibility of the primitives limit their outputs resolutions. Moreover, setting a sufficient number of primitives for an arbitrary shape is challenging. To overcome these issues, we propose ...


Mohsen Yavartanoo*

Jaeyoung Chung*

Reyhaneh Neshatavar

Kyoung Mu Lee



author = {Yavartanoo, Mohsen and Chung, Jaeyoung and Neshatavar, Reyhaneh and Lee, Kyoung Mu},

title = {3DIAS: 3D Shape Reconstruction With Implicit Algebraic Surfaces},

booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},

month = {October},

year = {2021},

pages = {12446-12455}}

You can freely acces to the PDF, code, poster, and check the citations via the following links.


Watch the video of our presentation in ICCV2021.

We propose a constrained implicit algebraic surface as the primitive with few learnable coefficients and higher geometrical complexities and a deep neural network to produce these primitives.

Whatch more videos on our YouTube channel.

3DIAS poseter presentation.

The remaining time to our presentation in ICCV2021.


Exprimental Results

Qualitative Comaprision

Qualitative comparison on single RGB image 3D shape reconstruction. SIF, AtlasNet, OccNet, CvxNet, and our 3DIAS output reconstructed 3D shape from the given RGB image. Comparison with other methods for the samples shown in CvxNet.

Complexity of primitives

Qualitative results on unsupervised semantic segmentation. We visualize the results of 3DIAS for some samples in the category of airplane.

Unsupervised Semantics Segmentation

The complexity of our primitives. The first and the second rows show the reconstructed shapes and their corresponding primitives for two samples. The proposed primitive can effectively present curved and torus shapes.