deep learning for interactive 3D scenes - how close are we actually

1. 1Explore NeRF and 3D Gaussian Splatting for novel view synthesis
2. 2Evaluate the limitations of current deep learning models for interactive 3D scenes
3. 3Investigate the challenges of achieving editable, physics-aware geometry in real-time
4. 4Apply deep learning techniques to specific use cases, such as game development or simulation
5. 5Test and refine the performance of deep learning models for interactive 3D scenes
6. 6Configure physics engines to work with deep learning-generated geometry

Developers and researchers working on 3D generation and interactive scenes can benefit from understanding the current ceiling of deep learning in this area, as it informs the design of their projects and the tools they use

💡 Current deep learning models for 3D generation are impressive for novel view synthesis, but struggle with editable, physics-aware geometry, highlighting the need for further research and development

💡 Deep learning for interactive 3D scenes: impressive for novel view synthesis, but falls short for editable, physics-aware geometry #3Dgeneration #deeplearning