Biometric identity provisioning allocates virtual face identities as non-colliding gaps within the real identity manifold, scaling to ten million embeddings and one million photorealistic images via gap-aware generation.
SapiensID 2.0 aligns human recognition with perception via soft-biometrics, noise disentanglement, and kinematic attention to achieve state-of-the-art re-identification and gait recognition.
LCVN introduces a language-conditioned navigation benchmark and compares diffusion-based latent imagination against unified autoregressive prediction for embodied agents. Latent imagination yields more temporally coherent rollouts, while unified prediction generalizes better to unseen environments.