NVIDIA

Harmonizer

Container

NVIDIA

Harmonizer

Harmonizer is a single-step image diffusion model trained as an online generative enhancer for neural-reconstruction image and video renderings.

Harmonizer Container Overview

Description:

This NIM container houses the Harmonizer model, which is a single-step image diffusion model trained as an online generative enhancer for neural-reconstruction image and video renderings. It transforms imperfect novel-view renderings produced by Neural Radiance Fields (NeRF) or 3D Gaussian Splatting (3DGS) reconstructions into temporally consistent outputs that are closer to real captures, while correcting illumination, shadow, and reconstruction-artifact issues that arise when dynamic objects are composited into reconstructed scenes.

The container components are ready for commercial use.

License/Terms of Use:

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 model is governed by the NVIDIA Open Model License Agreement.

You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.

Deployment Geography:

Global

Release Date:

Hugging Face 06/2026 via URL.

Program Class:

Model Name & Link	Use Case	How to Pull the Model
Harmonizer https://catalog.ngc.nvidia.com/orgs/nim/nvidia/models/Harmonizer/-	Online generative enhancer for neural-reconstruction image and video renderings.	Automatic

Deployment Details:

Visit the NIM Container Cosmos page for release documentation, deployment guides, and more.

Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.

Container Version(s):

nvcr.io/nim/nvidia/harmonizer:latest

Security Common Vulnerabilities and Exposures (CVEs)

Please review the Security Scanning tab on NGC to view the latest security scan results. For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. Developers should work with their internal developer team to ensure these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.

Users are responsible for model inputs and outputs. Users are responsible for ensuring safe integration of this model, including implementing guardrails as well as other safety mechanisms, prior to deployment.

Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

Get Help

Getting started with the NIM

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