Uniform Skeleton

Get the distribution q(x_t | x_0). :param x_start: the [N x C x ...] tensor of noiseless inputs. :param t: the number of dif

find the quaternion used to rotate v0 to v1

q0 : tensor of quaternions t: tensor of powers

Given a quaternion representing rotation, get the quaternion representing its inverse. Args: quaternion: Quaternions as tensor o

Convert rotations given as quaternions to axis/angle. Args: quaternions: quaternions with real part first, as tensor of

Generate random quaternions representing rotations, i.e. versors with nonnegative real part. Args: n: Number of quaternions in a

Generate random rotations as 3x3 rotation matrices. Args: n: Number of rotation matrices in a batch to return. dtype: Type t

Get Forward Direction

Converts 6D rotation representation by Zhou et al. [1] to rotation matrix using Gram--Schmidt orthogonalisation per Section B of [1]. Arg

Importance-sample timesteps for a batch. :param batch_size: the number of timesteps. :param device: the torch device to save

Create a list of timesteps to use from an original diffusion process, given the number of timesteps we want to take from equally-sized portio

Convert a unit quaternion to a standard form: one in which the real part is non negative. Args: quaternions: Quaternions with re

Update the reweighting using losses from a model. Sub-classes should override this method to update the reweighting using lo

Update the reweighting using losses from a model. Call this method from each rank with a batch of timesteps and the correspo

Get a numpy array of weights, one per diffusion step. The weights needn't be normalized, but must be positive.

Perform body fitting. Input: init_pose: SMPL pose estimate init_betas: SMPL betas estimate init_cam_t: Cam