2D to 3D can be the next AI revo | Dall e Image Generator Bing | Dall - e Mini | How to use Dalle 3 on mac | Turtles AI

  In a recent paper, #3DFuse is introduced as a #2D-to-3D #AI based technique. In recent days, the field of #text-to-3D generation has seen a rapid advancement with the introduction of #score #distillation, a #technique that uses #pretrained #text-to-2D #diffusion models to optimize #neural radiance field (#NeRF) in the zero-shot setting. However, despite its potential, score distillation-based methods have faced a significant challenge in reconstructing a plausible #3D scene due to the lack of 3D awareness in the #2D diffusion models. To overcome this challenge, a group of researchers has proposed a novel framework called 3DFuse. The framework incorporates 3D awareness into pre-trained 2D diffusion models, thereby enhancing the robustness and 3D consistency of score distillation-based methods. The researchers achieve this by first constructing a coarse 3D structure of a given text prompt and then utilizing projected, view-specific depth maps as a condition for the diffusion model. Additionally, they introduce a training strategy that enables the 2D diffusion model to handle errors and sparsity within the coarse 3D structure for a robust generation. They also ensure semantic consistency throughout all viewpoints of the scene. According to the researchers, 3DFuse surpasses the limitations of prior arts and has significant implications for 3D consistent generation of 2D diffusion models. Their experimental results demonstrate the effectiveness of the framework, outperforming previous models in quantitative metrics and qualitative human evaluation. This breakthrough in text-to-3D generation comes at a time when the demand for realistic 3D scenes is growing rapidly in various fields, including gaming, virtual reality, and augmented reality. With 3DFuse, researchers and developers now have a practical solution for addressing the limitations of current text-to-3D generation techniques and generating more realistic 3D scenes from text prompts.