At Motrix, we are dedicated to advancing the capture and generation of expressive human motion in 3D, with parametric human body models as a unified representation. We study the full lifecycle of human motion: from large-scale motion datasets and robust pose and shape estimation across diverse visual inputs, to controllable, physically plausible motion synthesis.

By bridging motion data, capture, and generation through shared representations and foundation models, Motrix aims to advance scalable, world-grounded human motion capture and generation across vision, graphics, and embodied AI.

• [2026-02-11] InfiniteDance, InsActor, MKA are now available on Motrix
• [2026-01-20] Release of ViMoGen (ICLR'26)
• [2026-01-20] Check out our expanded repos on motion generation and human motion dataset
• [2026-01-20] 🔥🔥🔥SMPLCap is now Motrix🔥🔥🔥
• [2026-01-07] PointHPS accepted to IJCV
• [2025-10-21] SMPLest-X accepted to TPAMI
• [2025-05-15] Release of ADHMR (ICML'25)
• [2025-04-11] Projects and homepage updated
• [2025-04-10] 🚀🚀🚀Announcing the launch of SMPLCap 🚀🚀🚀

• [SMPL-X] [TPAMI'25] SMPLest-X: An extended version of SMPLer-X with stronger foundation models.
• [SMPL-X] [NeurIPS'23] SMPLer-X: Scaling up EHPS towards a family of generalist foundation models.
• [SMPL-X] [ECCV'24] WHAC: World-grounded human pose and camera estimation from monocular videos.
• [SMPL-X] [CVPR'24] AiOS: An all-in-one-stage pipeline combining detection and 3D human reconstruction.
• [SMPL-X] [NeurIPS'23] RoboSMPLX: A framework to enhance the robustness of whole-body pose and shape estimation.
• [SMPL-X] [ICML'25] ADHMR: A framework to align diffusion-based human mesh recovery methods via direct preference optimization.
• [SMPL-X] MKA: Full-body 3D mesh reconstruction from single- or multi-view RGB videos.
• [SMPL] [ICCV'23] Zolly: 3D human mesh reconstruction from perspective-distorted images.
• [SMPL] [IJCV'26] PointHPS: 3D HPS from point clouds captured in real-world settings.
• [SMPL] [NeurIPS'22] HMR-Benchmarks: A comprehensive benchmark of HPS datasets, backbones, and training strategies.

• [SMPL-X] [ICLR'26] ViMoGen: A comprehensive framework that transfers knowledge from ViGen to MoGen across data, modeling, and evaluation.
• [SMPL-X] [ECCV'24] LMM: Large Motion Model for Unified Multi-Modal Motion Generation.
• [SMPL-X] [NeurIPS'23] FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing.
• [SMPL] InfiniteDance: A large-scale 3D dance dataset and an MLLM-based music-to-dance model designed for robust in-the-wild generalization.
• [SMPL] [NeurIPS'23] InsActor: Generating physics-based human motions from language and waypoint conditions via diffusion policies.
• [SMPL] [ICCV'23] ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model.
• [SMPL] [TPAMI'24] MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model.

• [SMPL] [ECCV'22] HuMMan: Toolbox for HuMMan, a large-scale multi-modal 4D human dataset.
• [SMPLX] [T-PAMI'24] GTA-Human: Toolbox for GTA-Human, a large-scale 3D human dataset generated with the GTA-V game engine.

For inquiries about our research, collaborations, or opportunities, please reach out to us.