3 papers
cs.CV2025
Granular Computing-driven SAM: From Coarse-to-Fine Guidance for Prompt-Free Segmentation
Qiyang Yu, Yu Fang, Tianrui Li +5
Prompt-free image segmentation aims to generate accurate masks without manual guidance. Typical pre-trained models, notably Segmentation Anything Model (SAM), generate prompts dire…
cs.CV2025
Dynamic Granularity Matters: Rethinking Vision Transformers Beyond Fixed Patch Splitting
Qiyang Yu, Yu Fang, Tianrui Li +4
Vision Transformers (ViTs) have demonstrated strong capabilities in capturing global dependencies but often struggle to efficiently represent fine-grained local details. Existing m…
cs.CV2025
High-Frequency Semantics and Geometric Priors for End-to-End Detection Transformers in Challenging UAV Imagery
Hongxing Peng, Lide Chen, Hui Zhu +1
Object detection in Unmanned Aerial Vehicle (UAV) imagery is fundamentally challenged by a prevalence of small, densely packed, and occluded objects within cluttered backgrounds. C…