Introduction:
OpenAI, the San Francisco-based AI powerhouse, has introduced its latest innovation in the form of Shap-E. This generative AI tool is capable of producing accurate three-dimensional objects from text prompts and is seen as yet another breakthrough after the success of Dall-E.
What is Shap-E?
Shap-E is a tool developed by OpenAI that uses neural radiance fields (NeRFs) to generate fine-grained textures and complex shapes from text inputs. It creates the shape and texture of the object by applying NeRFs to common diffusion models, which makes the process significantly faster than its predecessor, Point E.
Capabilities and Use Cases:
Shap-E has demonstrated its potential by generating 3D models such as a bowl of food, a penguin, and a campfire within seconds. The tool can be useful in various applications such as movies, virtual reality experiences, engineering simulations, and scientific research.
Output:
Although the tool is currently available for free on GitHub, the process of setting it up and running it is a challenging task. While Shap-E has a lot of potential, its output is still passable. Most outputs were low-res and lacked key details. Text inputs lead to outputs that were either colour-animated GIFs or monochrome PLY files that could be later opened in programs such as Paint 3D.
Conclusion:
Shap-E is an innovative tool that has the potential to revolutionize the domain of 3D modeling and rendering. While more precise samples of 3D output are awaited, Shap-E is a significant step forward in the field of text-to-3D model generation.
