5 citations · 7 across the 13 of their papers we have counts for
5 papers · 1 filter
Partial Weakly-Supervised Oriented Object Detection
Mingxin Liu, Peiyuan Zhang, Yuan Liu +8
The growing demand for oriented object detection (OOD) across various domains has driven significant research in this area. However, the high cost of dataset annotation remains a m…
When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning
Junwei Luo, Yingying Zhang, Xue Yang +5
Efficient vision-language understanding of large Remote Sensing Images (RSIs) is meaningful but challenging. Current Large Vision-Language Models (LVLMs) typically employ limited p…
Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detection
Yi Yu, Xue Yang, Yansheng Li +3
Accurately estimating the orientation of visual objects with compact rotated bounding boxes (RBoxes) has become a prominent demand, which challenges existing object detection parad…
Point2RBox-v2: Rethinking Point-supervised Oriented Object Detection with Spatial Layout Among Instances
Yi Yu, Botao Ren, Peiyuan Zhang +6
With the rapidly increasing demand for oriented object detection (OOD), recent research involving weakly-supervised detectors for learning OOD from point annotations has gained gre…
PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection
Peiyuan Zhang, Junwei Luo, Xue Yang +9
With the growing demand for oriented object detection (OOD), recent studies on point-supervised OOD have attracted significant interest. In this paper, we propose PointOBB-v3, a st…