3D Mesh Labeling via Deep Convolutional Neural Networks

@article{Guo20153DML,
  title={3D Mesh Labeling via Deep Convolutional Neural Networks},
  author={Kan Guo and Dongqing Zou and Xiaowu Chen},
  journal={ACM Trans. Graph.},
  year={2015},
  volume={35},
  pages={3:1-3:12}
}
This article presents a novel approach for 3D mesh labeling by using deep Convolutional Neural Networks (CNNs). Many previous methods on 3D mesh labeling achieve impressive performances by using predefined geometric features. However, the generalization abilities of such low-level features, which are heuristically designed to process specific meshes, are often insufficient to handle all types of meshes. To address this problem, we propose to learn a robust mesh representation that can adapt to… CONTINUE READING
Highly Cited
This paper has 87 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 45 extracted citations

87 Citations

0204060201620172018
Citations per Year
Semantic Scholar estimates that this publication has 87 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 14 references

Similar Papers

Loading similar papers…