5 citations · 8 across the 11 of their papers we have counts for
11 papers
Co-Training Vision Language Models for Remote Sensing Multi-task Learning
Qingyun Li, Shuran Ma, Junwei Luo +8
With Transformers achieving outstanding performance on individual remote sensing (RS) tasks, we are now approaching the realization of a unified model that excels across multiple t…
Point2RBox-v3: Self-Bootstrapping from Point Annotations via Integrated Pseudo-Label Refinement and Utilization
Teng Zhang, Ziqian Fan, Mingxin Liu +8
Driven by the growing need for Oriented Object Detection (OOD), learning from point annotations under a weakly-supervised framework has emerged as a promising alternative to costly…
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…
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…
A Simple Aerial Detection Baseline of Multimodal Language Models
Qingyun Li, Yushi Chen, Xinya Shu +4
The multimodal language models (MLMs) based on generative pre-trained Transformer are considered powerful candidates for unifying various domains and tasks. MLMs developed for remo…
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…
Exploiting Unlabeled Data with Multiple Expert Teachers for Open Vocabulary Aerial Object Detection and Its Orientation Adaptation
Yan Li, Weiwei Guo, Xue Yang +5
In recent years, aerial object detection has been increasingly pivotal in various earth observation applications. However, current algorithms are limited to detecting a set of pre-…
PointOBB-v2: Towards Simpler, Faster, and Stronger Single Point Supervised Oriented Object Detection
Botao Ren, Xue Yang, Yi Yu +2
Single point supervised oriented object detection has gained attention and made initial progress within the community. Diverse from those approaches relying on one-shot samples or…
STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery
Yansheng Li, Linlin Wang, Tingzhu Wang +11
Scene graph generation (SGG) in satellite imagery (SAI) benefits promoting understanding of geospatial scenarios from perception to cognition. In SAI, objects exhibit great variati…
PointOBB: Learning Oriented Object Detection via Single Point Supervision
Junwei Luo, Xue Yang, Yi Yu +3
Single point-supervised object detection is gaining attention due to its cost-effectiveness. However, existing approaches focus on generating horizontal bounding boxes (HBBs) while…