12 papers · 1 filter
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…
Learning Motion Blur Robust Vision Transformers for Real-Time UAV Tracking
You Wu, Xucheng Wang, Dan Zeng +4
Unmanned aerial vehicle (UAV) tracking is critical for applications like surveillance, search-and-rescue, and autonomous navigation. However, the high-speed movement of UAVs and ta…
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…
Learning an Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
You Wu, Yongxin Li, Mengyuan Liu +6
Transformer-based models have improved visual tracking, but most still cannot run in real time on resource-limited devices, especially for unmanned aerial vehicle (UAV) tracking. T…
Towards Reflected Object Detection: A Benchmark
Yiquan Wu, Zhongtian Wang, You Wu +3
Object detection has greatly improved over the past decade thanks to advances in deep learning and large-scale datasets. However, detecting objects reflected in surfaces remains an…
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…