Frontier Reports
State-of-the-field research on motion representation, generative video, embodied AI and body-to-model systems.
The Agnosticism Turn: Motion AI Is Removing Its Fixed Assumptions About Bodies, Sensors and Formats
The defining development in motion AI during July 2026 was the removal of fixed assumptions. Four independent research groups published systems that each dropped a constraint previously treated as structural: EquiFusion removed the fixed skeleton, WHIP removed the fixed sensor configuration, Two2Fou…
July 2026 Frontier Report: The Intent Layer — How Motion AI Discovered the Missing Middle
Across physics-based control, hierarchical tokenisation, and muscle-actuated modelling, June's research converges on a single insight: movement must be organised through an intermediate layer between abstract instruction and physical execution
June 2026 Frontier Report: CVPR Opens, the Taxonomy Turn, and 4D Interaction Generation
The field arrives at its largest conference yet with a clear agenda: from single-body visual generation toward multi-body, physics-grounded, semantically organised synthesis
May 2026 Frontier Report: Physics, Identity, and the Anticipatory Turn in Motion Generation
The field is moving from statistical motion completion toward causally grounded, physically plausible, and identity-aware synthesis
Manifold-Aware Motion Conditioning in Generative AI
The dominant conditioning paradigm in human motion generation treats pose as a flat array of joint positions—an $\mathbb{R}^{3J}$ vector for $J$ joints. The convenience is obvious: keypoints are easily supervised, trivially differentiable, and require no domain knowledge of kinematics. But this repr…