5 accepted papers
Driven by the imperative to leverage privacy-sensitive data scattered across decentralized devices, federated fine-tuning has emerged as a vital paradigm for adapting large language models without compromising data privacy. Yet, its practical efficacy is bottlenecked by severe client resource hetero…
Recent breakthroughs in Vision-Language Models (VLMs) have shown their capabilities in medical analysis tasks, but they remain limited in the brain lesion image domain, especially when pathological regions occupy a small portion of the image. The problem arises because VLMs are prone to put excessiv
In robotic surgery, instrument presence labels are typically recorded alongside video streams, offering a cost-effective alternative to manual annotations for segmentation tasks. Label-supervised surgical instrument segmentation (SIS), a weakly supervised segmentation setting where only instrument p
Anchor-based large-scale multi-view clustering has attracted considerable attention for its effectiveness in handling massive datasets. However current methods mainly seek the consensus embedding feature for clustering by exploring global correlations between anchor graphs or projection matrices.In…
The visual quality of point clouds has been greatly emphasized since the ever-increasing 3D vision applications are expected to provide cost-effective and high-quality experiences for users. Looking back on the development of point cloud quality assessment (PCQA), the visual quality is usually eval…