【论文精读】CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction - 代码天地

【论文精读】CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction

企业开发 2023-08-15 21:44:30 阅读次数: 0

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转载自blog.csdn.net/YuhsiHu/article/details/131924039

【论文精读】CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction

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【论文阅读】Rethinking Spatiotemporal Feature Learning For Video Understanding

Downsampled Imaging Geometric Modeling for Accurate CT Reconstruction via Deep Learning

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Geometric-Convolutional Feature Fusion Based on Learning Propagation for FacialExpressionRecognition

《论文阅读23》3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions

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Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction(中文翻译-机翻)

《Graph Representation Learning》【3】——Neighborhood Reconstruction Methods

3D Face Reconstruction

【ICML论文阅读】EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

【ICML论文阅读】EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

论文阅读——EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

【论文精读】MVSDF: Learning Signed Distance Field for Multi-view Surface Reconstruction

论文精读:PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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《Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network》论文学习笔记

论文阅读：Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

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