4 papers · 1 filter
Evaluating Intellectual Property Guardrails of Generative Image Models: A Technical Report
Austin T. Hoag, Apostolos Modas, Yunhao Ba +9
Generative image models are capable of producing images that bear a strong resemblance to, or replicate, recognizable intellectual property (IP). In this technical report, we prese…
An Augmentation-based Model Re-adaptation Framework for Robust Image Segmentation
Zheming Zuo, Joseph Smith, Jonathan Stonehouse +1
Image segmentation is a crucial task in computer vision, with wide-ranging applications in industry. The Segment Anything Model (SAM) has recently attracted intensive attention; ho…
Robust and Explainable Fine-Grained Visual Classification with Transfer Learning: A Dual-Carriageway Framework
Zheming Zuo, Joseph Smith, Jonathan Stonehouse +1
In the realm of practical fine-grained visual classification applications rooted in deep learning, a common scenario involves training a model using a pre-existing dataset. Subsequ…
How Quality Affects Deep Neural Networks in Fine-Grained Image Classification
Joseph Smith, Zheming Zuo, Jonathan Stonehouse +1
In this paper, we propose a No-Reference Image Quality Assessment (NRIQA) guided cut-off point selection (CPS) strategy to enhance the performance of a fine-grained classification…