Guidance Parameters

For calibration math, see Calibration Math.

Overview

After the diffusion model predicts a pose sequence, a Levenberg-Marquardt optimizer refines it to be physically plausible and consistent with sensor readings. The optimizer runs twice: once between denoising steps (inner, 5 iterations) and once after sampling is complete (post, 20 iterations).

Shared Constraints (All Modes)

These constraints are applied in every guidance mode, including pure egoallo:

Constraint	Weight	What it does
Pose prior	1.0	Keeps joint rotations close to the diffusion output
Torso prior	5.0	Keeps torso joint positions close to the diffusion output
Delta smoothness	10.0	Prevents large frame-to-frame changes in the optimizer correction
Velocity smoothness	5.0	Penalizes acceleration in joint rotations (reduces jitter)
Foot skating	30.0	Prevents foot joints from sliding when contact is predicted

IMU Constraints (RoSHI Modes)

These are added in roshi and roshi_ariahand modes:

Constraint	Weight	What it does
Local joint matching	5.0	Each IMU-equipped joint rotation should match its IMU reading
Pelvis rotation matching	5.0	Frame-to-frame pelvis rotation change should match the pelvis IMU
Body prior	0.1	Extra prior to keep IMU-guided poses near the diffusion output
Body smoothness	10.0	Extra temporal smoothing for body joints

Local joint matching minimizes the geodesic distance between predicted and IMU-derived parent-relative rotations:

\[\mathcal{L}_{\text{local}} = \sum_{j \in \mathcal{J}_{\text{IMU}}} \left\lVert \log\!\left( \hat{R}_{j}^{\top} \cdot R_{j}^{\text{IMU}} \right) \right\rVert^{2}\]

Pelvis rotation matching:

\[\mathcal{L}_{\text{pelvis}} = \sum_{t} \left\lVert \log\!\left( \Delta \hat{R}_{\text{pelvis}}^{\top}(t) \cdot \Delta R_{\text{pelvis}}^{\text{IMU}}(t) \right) \right\rVert^{2}\]

Body smoothness penalizes large frame-to-frame rotation changes:

\[\mathcal{L}_{\text{smooth}} = \sum_{t} \sum_{j} \left\lVert \log\!\left( \hat{R}_{j}(t)^{\top} \cdot \hat{R}_{j}(t{+}1) \right) \right\rVert^{2}\]