5 papers · 1 filter
Corner2Net: Detecting Objects as Cascade Corners
Chenglong Liu, Jintao Liu, Haorao Wei +4
The corner-based detection paradigm enjoys the potential to produce high-quality boxes. But the development is constrained by three factors: 1) Hard to match corners. Heuristic cor…
DynamicTrack: Advancing Gigapixel Tracking in Crowded Scenes
Yunqi Zhao, Yuchen Guo, Zheng Cao +3
Tracking in gigapixel scenarios holds numerous potential applications in video surveillance and pedestrian analysis. Existing algorithms attempt to perform tracking in crowded scen…
SaccadeDet: A Novel Dual-Stage Architecture for Rapid and Accurate Detection in Gigapixel Images
Wenxi Li, Ruxin Zhang, Haozhe Lin +3
The advancement of deep learning in object detection has predominantly focused on megapixel images, leaving a critical gap in the efficient processing of gigapixel images. These su…
Debiased Novel Category Discovering and Localization
Juexiao Feng, Yuhong Yang, Yanchun Xie +6
In recent years, object detection in deep learning has experienced rapid development. However, most existing object detection models perform well only on closed-set datasets, ignor…
PANDA: A Gigapixel-level Human-centric Video Dataset
Xueyang Wang, Xiya Zhang, Yinheng Zhu +8
We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapi…