This project page contains a ResNet-101 deep network model for 3DMM regression (3D shape and texture)

The download includes both the network itself and the parameters required to map the 3DMM parameters regressed by the network back to 3D shapes
(e.g., the basis vectors for the face shape and the average face shape).

If you find this useful, please remember to cite of paper below:

latex<br/>@inproceedings{tran2017regressing,<br/> title={Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network},<br/> author={Tran, Anh Tuan and Hassner, Tal and Masi, Iacopo and Medioni, G'{e}rard},<br/> booktitle={Computer Vision and Pattern Recognition (CVPR)},<br/> year={2017}<br/>}<br/>

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