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NVIDIA
body-pose
Container
NVIDIA
body-pose

The 3D Body Pose NIM estimates 3D human body pose and skeleton from video input using GPU-accelerated inference. It processes video frames through a Triton Inference Server backend and returns pose estimation results via a gRPC streaming API.

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What Is NVIDIA NIM?

NVIDIA NIM™, part of NVIDIA AI Enterprise, is a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing across clouds, data centers and workstations. Supporting a wide range of AI models, including open-source and NVIDIA AI Foundation and custom models, it ensures seamless, scalable AI inferencing, on-premises or in the cloud, leveraging industry standard APIs.

The 3D Body Pose NIM uses GPU-accelerated inference to estimate 3D human body poses and skeletal structures from video input. It processes video frames using an NVIDIA Triton Inference Server backend and returns pose-estimation results through a streaming gRPC API.

NVIDIA NIM offers prebuilt containers for computer vision models. Each NIM consists of a container and a model and uses a CUDA-accelerated runtime for all NVIDIA GPUs, with special optimizations available for many configurations. Whether on-premises or in the cloud, NIM is the fastest way to achieve accelerated inference at scale.

Getting started with NVIDIA NIM

Deploying and integrating NVIDIA NIM is straightforward thanks to our industry standard APIs. Visit the Body Pose NIM page for release documentation, deployment guides and more.

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Governing Terms

Use of this container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for NVIDIA AI Products. Use of the Gemno model is governed by the NVIDIA Open Model License Agreement. Use of the Vitpose model is governed by the NVIDIA Open Model License Agreement, the Meta Dinov3 License and the SAM License; Built with Dinov3. Use of the SAM3DB-Body model is governed by the NVIDIA Open Model License Agreement and the SAM License.

Publisher
NVIDIA
Latest Tag1.0
UpdatedOctober 1, 2026 UTC
Compressed Size5.21 GB
Multinode SupportNo
Multi-Arch SupportNo

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