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About this paper
Ben Kang, Xin Chen, Dong Wang, Houwen Peng, Huchuan Lu
The Hierarchical Vision Transformer (HiT) family of models provides efficient visual tracking, achieving state-of-the-art performance among real-time trackers while operating at speeds up to 77 frames per second on Nvidia Jetson AGX edge devices. This is accomplished by integrating lightweight hierarchical transformers with a novel Bridge Module for multi-level feature fusion and a dual-image position encoding scheme.
Key insights
- Aggressive downsampling in efficient hierarchical transformers can be effectively compensated for by a simple yet robust multi-stage feature fusion module, preserving critical fine-grained details for tracking.
- Explicitly encoding the relative positions between template and search regions in a non-overlapping manner (e.g., diagonally) significantly enhances a transformer's ability to spatially reason between objects.
- High accuracy and real-time inference speed on edge devices for transformer-based visual tracking are achievable by combining optimized lightweight backbones with targeted architectural innovations like the Bridge Module and dual-image position encoding.
Summary by alphaXiv.
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