Search Results for author: Yan-Pei Cao

Found 4 papers, 3 papers with code

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

1 code implementation ICCV 2021 Peng Xiang, Xin Wen, Yu-Shen Liu, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Zhizhong Han

However, previous methods usually suffered from discrete nature of point cloud and unstructured prediction of points in local regions, which makes it hard to reveal fine local geometric details on the complete shape.

Point Cloud Completion

Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding

1 code implementation CVPR 2021 Xin Wen, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu

We provide a comprehensive evaluation in experiments, which shows that our model with the learned bidirectional geometry correspondence outperforms state-of-the-art unpaired completion methods.

Point Cloud Completion

PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths

1 code implementation CVPR 2021 Xin Wen, Peng Xiang, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, Yu-Shen Liu

As a result, the network learns a strict and unique correspondence on point-level, which can capture the detailed topology and structure relationships between the incomplete shape and the complete target, and thus improves the quality of the predicted complete shape.

Point Cloud Completion

Learning to Reconstruct High-quality 3D Shapes with Cascaded Fully Convolutional Networks

no code implementations ECCV 2018 Yan-Pei Cao, Zheng-Ning Liu, Zheng-Fei Kuang, Leif Kobbelt, Shi-Min Hu

We present a data-driven approach to reconstructing high-resolution and detailed volumetric representations of 3D shapes.

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