5 papers
VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment
Zi Wang, Katsuya Hotta, Yawen Zou +4
Few-shot cross-category 3D anomaly detection aims to determine whether an unknown point cloud belongs to a target normal category using only a few normal references. Existing train…
Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation
Qilong Zhang, Youheng Sun, Chaoning Zhang +4
In recent years, the adversarial vulnerability of deep neural networks (DNNs) has raised increasing attention. Among all the threat models, no-box attacks are the most practical bu…
Text-to-image Diffusion Models in Generative AI: A Survey
Chenshuang Zhang, Chaoning Zhang, Mengchun Zhang +2
This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts wit…
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…
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…