NVIDIA (with ETH Zürich, Simon Fraser University and the University of Texas at Austin) · Real-time motion generation

MotionBricks

Since Week 19 2026: MotionBricks is a real-time generative framework for character motion from NVIDIA, published in ACM Transactions on Graphics (SIGGRAPH 2026). It pairs a modular latent generative backbone with 'smart primitives', an interface for authoring navigation (smart locomotion) and object interaction (smart objects, specified as proxy keyframes). The authors report 15,000 FPS and 2 ms latency, with a single model covering a dataset of over 350,000 motion clips. They say it applies to new downstream tasks zero-shot, with no fine-tuning or task-specific tagging. The project page shows a 2:40 uncut Unreal Engine 5 demo and in-betweening comparisons against six baselines, though no numerical comparison results are given in the page. The code is available at NVlabs/motionbricks, with a runtime (Warp, Newton and TensorRT backends), pretrained SOMA and Unitree G1 models (ONNX bundled, SafeTensors checkpoints on Hugging Face), an ONNX exporter, interactive demos and editors. It is also part of NVIDIA's GR00T Whole-Body Control stack, and the training corpus is the BONES-SEED dataset. The page does not state a licence.