5 papers · 1 filter
Argus-Unified: Towards A Compact and Economical Unified Model for Image Understanding and Generation
Weiming Zhuang, Jiabo Huang, Jingtao Li +4
Unifying visual understanding and generation in one model holds immense promise, but remains challenging and expensive due to heavy compute and data demands and conflicts between t…
Empirical Recipes for Efficient and Compact Vision-Language Models
Jiabo Huang, Zhizhong Li, Sina Sajadmanesh +2
Deploying vision-language models (VLMs) in resource-constrained settings demands low latency and high throughput, yet existing compact VLMs often fall short of the inference speedu…
CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI
Siyuan Cheng, Lingjuan Lyu, Zhenting Wang +2
With the rapid advancement of generative AI, it is now possible to synthesize high-quality images in a few seconds. Despite the power of these technologies, they raise significant…
Rendering-Refined Stable Diffusion for Privacy Compliant Synthetic Data
Kartik Patwari, David Schneider, Xiaoxiao Sun +3
Growing privacy concerns and regulations like GDPR and CCPA necessitate pseudonymization techniques that protect identity in image datasets. However, retaining utility is also esse…
Activity Recognition on Avatar-Anonymized Datasets with Masked Differential Privacy
David Schneider, Sina Sajadmanesh, Vikash Sehwag +4
Privacy-preserving computer vision is an important emerging problem in machine learning and artificial intelligence. Prevalent methods tackling this problem use differential privac…