1 citations · 1 across the 5 of their papers we have counts for
6 papers
SBMVTrack: Spike-Budgeted Multi-View Learning for Power-Efficient UAV Tracking
Pengzhi Zhong, Jiwei Mo, Haolun Li +4
With sparse and event-driven computation, spiking neural networks show great potential for achieving accurate and power-efficient UAV visual tracking. However, existing SNN-based t…
STATrack: A Target-Aware Fully Spiking Neural Network for Efficient UAV Tracking
Pengzhi Zhong, Jiwei Mo, Dan Zeng +2
Spiking Neural Networks (SNNs), characterized by their event-driven computation and low power consumption, have shown great potential for energy-efficient visual tracking on unmann…
SMTrack: End-to-End Trained Spiking Neural Networks for Multi-Object Tracking in RGB Videos
Pengzhi Zhong, Xinzhe Wang, Dan Zeng +3
Brain-inspired Spiking Neural Networks (SNNs) exhibit significant potential for low-power computation, yet their application in visual tasks remains largely confined to image class…
Low-Light Object Tracking: A Benchmark
Pengzhi Zhong, Xiaoyu Guo, Defeng Huang +4
In recent years, the field of visual tracking has made significant progress with the application of large-scale training datasets. These datasets have supported the development of…
Camouflaged Object Tracking: A Benchmark
Xiaoyu Guo, Pengzhi Zhong, Hao Zhang +4
Visual tracking has seen remarkable advancements, largely driven by the availability of large-scale training datasets that have enabled the development of highly accurate and robus…
Tracking Reflected Objects: A Benchmark
Xiaoyu Guo, Pengzhi Zhong, Lizhi Lin +3
Visual tracking has advanced significantly in recent years, mainly due to the availability of large-scale training datasets. These datasets have enabled the development of numerous…