Skip to Main content Skip to Navigation
Conference papers

An Effective Loss Function for Generating 3D Models from Single 2D Image Without Rendering

Abstract : Differentiable rendering is a very successful technique that applies to a Single-View 3D Reconstruction. Current renderers use losses based on pixels between a rendered image of some 3D reconstructed object and ground-truth images from given matched viewpoints to optimise parameters of the 3D shape.These models require a rendering step, along with visibility handling and evaluation of the shading model. The main goal of this paper is to demonstrate that we can avoid these steps and still get reconstruction results as other state-of-the-art models that are equal or even better than existing category-specific reconstruction methods. First, we use the same CNN architecture for the prediction of a point cloud shape and pose prediction like the one used by Insafutdinov & Dosovitskiy. Secondly, we propose the novel effective loss function that evaluates how well the projections of reconstructed 3D point clouds cover the ground-truth object’s silhouette. Then we use Poisson Surface Reconstruction to transform the reconstructed point cloud into a 3D mesh. Finally, we perform a GAN-based texture mapping on a particular 3D mesh and produce a textured 3D mesh from a single 2D image. We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
Document type :
Conference papers
Complete list of metadata

https://hal.inria.fr/hal-03287660
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Thursday, July 15, 2021 - 6:09:47 PM
Last modification on : Thursday, July 15, 2021 - 6:34:45 PM
Long-term archiving on: : Saturday, October 16, 2021 - 7:02:53 PM

File

 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : 2024-01-01

Please log in to resquest access to the document

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Nikola Zubić, Pietro Liò. An Effective Loss Function for Generating 3D Models from Single 2D Image Without Rendering. 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2021, Hersonissos, Crete, Greece. pp.309-322, ⟨10.1007/978-3-030-79150-6_25⟩. ⟨hal-03287660⟩

Share

Metrics

Record views

16