instant-nurec

Instant-NuRec | Model Card Code** | **Model** Description: Instant-NuRec is a model that takes a series of images as input and outputs Gaussian Splats. The model uses an alternate-attention Vision Transformer encoder following the Depth-Anything-v3 (DAv3) design and is initialized from the DAv3 ViT-Base checkpoint (DINOv2-based) before being finetuned on NVIDIA AV data. Instant-NuRec allows users to generate Gaussian Splats in less than 2 minutes. This model was trained to take up to 90 input images (5 views x 18 frames) with a resolution of 504x280. This model is ready for commercial/non-commercial use. Support 📣 **Instant Nurec usage questions**: post on the NVIDIA Developer Forum (Omniverse / NuRec). 🐛 **Instant Nurec code bugs / documentation issues / feature requests**: file a GitHub issue using the appropriate template (Bug report, Documentation request, or Feature request) at https://github.com/NVIDIA/instant-nurec/issues . The relevant NVIDIA responder is auto-assigned. 🚨 **Security vulnerabilities**: please use NVIDIA's Vulnerability Disclosure Program. Do not file public issues. (Note: the Hugging Face Community tab for the Instant Nurec model will be disabled on 08/04/2026. Please use the channels above.)* License/Terms of Use: Governing Terms: Use of this model system is governed by the NVIDIA Open Model License Agreement. Deployment Geography: Global Release Management: Instant-NuRec is published as a standalone GitHub repository for code, with model weights distributed via Hugging Face. Release date: June 2026 GitHub code: https://github.com/NVIDIA/instant-nurec Hugging Face model and weights: https://huggingface.co/nvidia/instant-nurec Use Case: Physical AI developers who are looking to create 3D automotive scenes for either closed-loop simulation or Synthetic Data Generation (SDG). Known Technical Limitations: The model is not guaranteed to perform well with scenes that are outside of the common distribution. The model was not trained on extreme weat