microsoft / Deep3DFaceReconstruction

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set (CVPRW 2019)
MIT License
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关于point_buf和顶点法线计算 #209

Open HITKevin opened 1 year ago

HITKevin commented 1 year ago
def Compute_norm(self, face_shape):

        face_id = self.tri.long()
        point_id = self.point_buf.long()
        shape = face_shape
        v1 = shape[:, face_id[:, 0], :]
        v2 = shape[:, face_id[:, 1], :]
        v3 = shape[:, face_id[:, 2], :]
        e1 = v1 - v2
        e2 = v2 - v3
        face_norm = e1.cross(e2)
        empty = torch.zeros((face_norm.size(0), 1, 3),
                            dtype=face_norm.dtype, device=face_norm.device)
        face_norm = torch.cat((face_norm, empty), 1)
        v_norm = face_norm[:, point_id, :].sum(2)
        v_norm = v_norm / v_norm.norm(dim=2).unsqueeze(2)

        return v_norm

为什么不把empty cat在前边,这样point_buf里的index也不用-1了,而且这样用0补齐(N,8)就可以了,也不会有让人难以理解的以面的个数作为占位数字补齐

yuchen814 commented 1 year ago

请问如果我想重建耳朵和脖子部分,怎么建立53215维度的point_buf啊

WangXuan2401 commented 1 year ago

请问如果我想重建耳朵和脖子部分,怎么建立53215维度的point_buf啊

hello,Have you solved the problem?I met the same problem when getting full region with neck and ears, would you be nice to give me some help? thanks for your attention