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Jonathan Lorraine

lorraine2

https://www.jonlorraine.com/

AI & ML interests

machine learning, computer vision, generative AI

Recent Activity

posted an update 6 days ago

🔊 New NVIDIA paper: Audio-SDS 🔊 We adapt Score Distillation Sampling (SDS), originally developed for text-to-3D generation, to audio diffusion models, allowing us to reuse large pretrained models for new text-guided parametric audio tasks such as source separation, physically informed impact synthesis, and more. 🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/Audio-SDS/ 📖 Full Paper: https://arxiv.org/abs/2505.04621 Check out more from NVIDIA’s Spatial Intelligence Lab here: https://research.nvidia.com/labs/toronto-ai/ This project was led by the great work of Jessie Richter-Powell, along with Antonio Torralba. Notably, we find a new and exciting use case for Stable Audio Open 🚀

authored a paper 5 months ago

Multi-student Diffusion Distillation for Better One-step Generators

posted an update 5 months ago

🦙New NVIDIA paper: LLaMA-Mesh 🦙 We enable large language models to generate and understand 3D meshes by representing them as text and fine-tuning. This unifies the 3D and text modalities in a single model and preserves language abilities, unlocking conversational 3D creation with mesh understanding. 🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/LLaMA-Mesh/ 🕹️ Interactive Demo: https://huggingface.co/spaces/Zhengyi/LLaMA-Mesh (courtesy of HuggingFace and Gradio) 📖 Full Paper: https://arxiv.org/abs/2411.09595 👨‍💻Code: https://github.com/nv-tlabs/LLaMa-Mesh 💾 Model Checkpoint: https://huggingface.co/Zhengyi/LLaMA-Mesh 🧩 Blender Addon: https://github.com/huggingface/meshgen (courtesy of Dylan Ebert) 🎥 5-min Overview Video: https://youtu.be/eZNazN-1lPo?si=-idQa5aaceVw0Bbj (courtesy of AI Papers Academy)

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498

🔊 New NVIDIA paper: Audio-SDS 🔊

We adapt Score Distillation Sampling (SDS), originally developed for text-to-3D generation, to audio diffusion models, allowing us to reuse large pretrained models for new text-guided parametric audio tasks such as source separation, physically informed impact synthesis, and more.

🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/Audio-SDS/
📖 Full Paper: https://arxiv.org/abs/2505.04621

Check out more from NVIDIA’s Spatial Intelligence Lab here: https://research.nvidia.com/labs/toronto-ai/

This project was led by the great work of Jessie Richter-Powell, along with Antonio Torralba.

Notably, we find a new and exciting use case for Stable Audio Open 🚀

Post

2013

🦙New NVIDIA paper: LLaMA-Mesh 🦙

We enable large language models to generate and understand 3D meshes by representing them as text and fine-tuning. This unifies the 3D and text modalities in a single model and preserves language abilities, unlocking conversational 3D creation with mesh understanding.

🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/LLaMA-Mesh/
🕹️ Interactive Demo: Zhengyi/LLaMA-Mesh (courtesy of HuggingFace and Gradio)
📖 Full Paper: https://arxiv.org/abs/2411.09595
👨‍💻Code: https://github.com/nv-tlabs/LLaMa-Mesh
💾 Model Checkpoint: Zhengyi/LLaMA-Mesh
🧩 Blender Addon: https://github.com/huggingface/meshgen (courtesy of Dylan Ebert)
🎥 5-min Overview Video: https://youtu.be/eZNazN-1lPo?si=-idQa5aaceVw0Bbj (courtesy of AI Papers Academy)

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