Stable Zero123

Overview

Stable Zero123 is an internally developed model for view-conditioned image generation, designed to address the limitations of its predecessor, Zero123-XL. The enhanced version introduces three groundbreaking innovations that set it apart from previous models:

1. Curated Training Dataset

The foundation of Stable Zero123 lies in a meticulously filtered training dataset derived from Objaverse. Unlike earlier versions, this model exclusively utilizes high-quality 3D objects, rendered with unprecedented realism. This stringent selection process ensures that only the most accurate and visually consistent data is used for training.

2. Camera Angle Integration

A unique feature of Stable Zero123 is its ability to incorporate estimated camera angles during both the training and inference phases. By receiving this additional information, the model gains a spatial awareness that significantly enhances the quality and accuracy of generated images.

3. Efficient Training Pipeline

To optimize performance, Stable Zero123 employs precomputed datasets (latent variables) and an advanced data loader that supports larger batch sizes. When combined with the enhanced dataset from Objaverse, this results in a remarkable 40x improvement in training efficiency compared to Zero123-XL.

Target Users

The primary audience for Stable Zero123 includes:

Researchers and Academics

Investigators in the field of 3D object generation will find this model particularly valuable. It provides a robust toolset for conducting cutting-edge research in image synthesis and view-conditioned rendering.

Non-Commercial Users

Available on Hugging Face, Stable Zero123 offers researchers and non-commercial entities an accessible platform to experiment with advanced 3D object generation techniques.

Use Cases

The versatility of Stable Zero123 extends across multiple applications:

Research Institutions

Leading research organizations can leverage this model to advance their work in 3D object synthesis and image generation technologies.

Academic Experimentation

Educational institutions can utilize Stable Zero123 for conducting detailed experiments in view-conditioned image generation, enhancing both theoretical understanding and practical skills.

Community Discussions

The developer community is encouraged to discuss and explore the capabilities of Stable Zero123 in generating high-quality 3D objects. This fosters collaborative innovation and knowledge sharing within the field.

Features

Stable Zero123 offers two core functionalities:

High-Quality 3D Object Generation

The model’s ability to generate highly detailed and realistic 3D objects makes it a powerful tool for researchers and developers.

Support for View-Conditioned Image Generation

By incorporating camera angle information during both training and inference, Stable Zero123 excels in generating images that accurately reflect specified viewpoints.