109 citations · 179 across the 12 of their papers we have counts for
3 papers · 1 filter
DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Sampling
Haoran Li, Haolin Shi, Wenli Zhang +5
Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high qu…
A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering
Chaoning Zhang, Joseph Cho, Fachrina Dewi Puspitasari +11
The Segment Anything Model (SAM), developed by Meta AI Research, represents a significant breakthrough in computer vision, offering a robust framework for image and video segmentat…
Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era
Chenghao Li, Chaoning Zhang, Joseph Cho +6
Generative AI has made significant progress in recent years, with text-guided content generation being the most practical as it facilitates interaction between human instructions a…