Visual prompt engineering is a fundamental methodology in the field of visual and image
artificial general intelligence. As the development of large vision models progresses, the …

Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

Deep learning-based medical image segmentation models often suffer from domain shift,
where the models trained on a source domain do not generalize well to other unseen …

Zero-shot 6D object pose estimation involves the detection of novel objects with their 6D
poses in cluttered scenes presenting significant challenges for model generalizability …

In this study, we evaluate the performance of the Segment Anything Model (SAM) model in
clinical radiotherapy. We collected real clinical cases from four regions at the Mayo Clinic …

In this paper we propose a novel Visual Reference Prompt (VRP) encoder that empowers
the Segment Anything Model (SAM) to utilize annotated reference images as prompts for …

Segment anything model (SAM) has presented impressive objectness identification
capability with the idea of prompt learning and a new collected large-scale dataset. Given a …

In image restoration (IR) leveraging semantic priors from segmentation models has been a
common approach to improve performance. The recent segment anything model (SAM) has …

Deep recognition models are widely vulnerable to adversarial examples, which change the
model output by adding quasi-imperceptible perturbation to the image input. Recently …