48 citations · 85 across the 5 of their papers we have counts for
5 papers
Drift-Resilient Temporal Priors for Visual Tracking
Yuqing Huang, Liting Lin, Weijun Zhuang +2
Temporal information is crucial for visual tracking, but existing multi-frame trackers are vulnerable to model drift caused by naively aggregating noisy historical predictions. In…
Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
Liting Lin, Heng Fan, Zhipeng Zhang +3
Motivated by the Parameter-Efficient Fine-Tuning (PEFT) in large language models, we propose LoRAT, a method that unveils the power of large ViT model for tracking within laborator…
SwinTrack: A Simple and Strong Baseline for Transformer Tracking
Liting Lin, Heng Fan, Zhipeng Zhang +2
Recently Transformer has been largely explored in tracking and shown state-of-the-art (SOTA) performance. However, existing efforts mainly focus on fusing and enhancing features ge…
LaSOT: A High-quality Large-scale Single Object Tracking Benchmark
Heng Fan, Hexin Bai, Liting Lin +11
Despite great recent advances in visual tracking, its further development, including both algorithm design and evaluation, is limited due to lack of dedicated large-scale benchmark…
LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking
Heng Fan, Liting Lin, Fan Yang +7
In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame…