![]() ![]() After NeoGeo's dissolution, Ton Roosendaal founded Not a Number Technologies (NaN) in June 1998 to further develop Blender, initially distributing it as shareware until NaN went bankrupt in 2002. NeoGeo was later dissolved, and its client contracts were taken over by another company. On January 1, 1998, Blender was released publicly online as SGI freeware. ![]() Some design choices and experiences for Blender were carried over from an earlier software application, called Traces, that Roosendaal developed for NeoGeo on the Commodore Amiga platform during the 1987–1991 period. The name Blender was inspired by a song by the Swiss electronic band Yello, from the album Baby, which NeoGeo used in its showreel. Version 1.00 was released in January 1995, with the primary author being company co-owner and software developer Ton Roosendaal. Our approach requires no 3D training data and no modifications to the image diffusion model, demonstrating the effectiveness of pretrained image diffusion models as priors.The Dutch animation studio NeoGeo (not related to the Neo Geo family of video game hardware) started to develop Blender as an in-house application, and based on the timestamps for the first source files, Januis considered to be Blender's birthday. The resulting 3D model of the given text can be viewed from any angle, relit by arbitrary illumination, or composited into any 3D environment. Using this loss in a DeepDream-like procedure, we optimize a randomly-initialized 3D model (a Neural Radiance Field, or NeRF) via gradient descent such that its 2D renderings from random angles achieve a low loss. We introduce a loss based on probability density distillation that enables the use of a 2D diffusion model as a prior for optimization of a parametric image generator. ![]() In this work, we circumvent these limitations by using a pretrained 2D text-to-image diffusion model to perform text-to-3D synthesis. Adapting this approach to 3D synthesis would require large-scale datasets of labeled 3D assets and efficient architectures for denoising 3D data, neither of which currently exist. Recent breakthroughs in text-to-image synthesis have been driven by diffusion models trained on billions of image-text pairs. ![]()
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