def rot6d_to_rotmat(x):
    """Convert 6D rotation representation to 3x3 rotation matrix.

    Based on Zhou et al., "On the Continuity of Rotation
    Representations in Neural Networks", CVPR 2019
    Input:
        (B,6) Batch of 6-D rotation representations
    Output:
        (B,3,3) Batch of corresponding rotation matrices
    """
    x = x.view(-1, 3, 2)
    a1 = x[:, :, 0]
    a2 = x[:, :, 1]
    b1 = F.normalize(a1)
    b2 = F.normalize(a2 - torch.einsum('bi,bi->b', b1, a2).unsqueeze(-1) * b1)
    b3 = torch.cross(b1, b2)
    return torch.stack((b1, b2, b3), dim=-1)
Convert 6D rotation representation to 3x3 rotation matrix.

    Based on Zhou et al., "On the Continuity of Rotation
    Representations in Neural Networks", CVPR 2019
    Input:
        (B,6) Batch of 6-D rotation representations
    Output:
        (B,3,3) Batch of corresponding rotation matrices
    
mmpose/mmpose/models/utils/geometry.py