3D Content Creation
3D content creation research focuses on efficiently generating high-quality three-dimensional models and scenes from various inputs like text, single images, or sparse views. Current efforts center on developing novel deep learning architectures, including diffusion models and generative adversarial networks (GANs), often incorporating techniques like Gaussian splatting and multi-view consistency to improve realism and speed. These advancements are significantly impacting fields such as virtual and augmented reality, gaming, and digital heritage preservation by automating and accelerating the traditionally laborious process of 3D asset creation. Furthermore, interactive systems are being developed to provide users with greater control over the generation process.
Papers
HyperDreamer: Hyper-Realistic 3D Content Generation and Editing from a Single Image
Tong Wu, Zhibing Li, Shuai Yang, Pan Zhang, Xinggang Pan, Jiaqi Wang, Dahua Lin, Ziwei Liu
Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes
Hmrishav Bandyopadhyay, Subhadeep Koley, Ayan Das, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song