Paper ID: 2410.16329

The Solution for Single Object Tracking Task of Perception Test Challenge 2024

Zhiqiang Zhong, Yang Yang, Fengqiang Wan, Henglu Wei, Xiangyang Ji

This report presents our method for Single Object Tracking (SOT), which aims to track a specified object throughout a video sequence. We employ the LoRAT method. The essence of the work lies in adapting LoRA, a technique that fine-tunes a small subset of model parameters without adding inference latency, to the domain of visual tracking. We train our model using the extensive LaSOT and GOT-10k datasets, which provide a solid foundation for robust performance. Additionally, we implement the alpha-refine technique for post-processing the bounding box outputs. Although the alpha-refine method does not yield the anticipated results, our overall approach achieves a score of 0.813, securing first place in the competition.

Submitted: Oct 19, 2024