Papers › Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline

Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline

8 Apr 2022CVPR 2022 1arXiv:2204.04120archive 2025-07-28

Pengyu Zhang, Jie Zhao, Dong Wang, Huchuan Lu, Xiang Ruan

With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to achieve robust performance and wider application scenarios with the guidance of objects' temperature information. However, the lack of paired training samples is the main bottleneck for unlocking the power of RGB-T tracking. Since it is laborious to collect high-quality RGB-T sequences, recent benchmarks only provide test sequences. In this paper, we construct a large-scale benchmark with high diversity for visible-thermal UAV tracking (VTUAV), including 500 sequences with 1.7 million high-resolution (1920 × 1080 pixels) frame pairs. In addition, comprehensive applications (short-term tracking, long-term tracking and segmentation mask prediction) with diverse categories and scenes are considered for exhaustive evaluation. Moreover, we provide a coarse-to-fine attribute annotation, where frame-level attributes are provided to exploit the potential of challenge-specific trackers. In addition, we design a new RGB-T baseline, named Hierarchical Multi-modal Fusion Tracker (HMFT), which fuses RGB-T data in various levels. Numerous experiments on several datasets are conducted to reveal the effectiveness of HMFT and the complement of different fusion types. The project is available at here.

PaperPDFConference PDFCode

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

zhang-pengyu/HMFT officialmentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

AttributeDiversityObject TrackingRgb-T Tracking

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Rgb-T Tracking GTOT HMFT Precision 91.2 #9 of 15 Archive leaderboard report
Rgb-T Tracking GTOT HMFT Success 74.9 #9 of 15 Archive leaderboard report
Rgb-T Tracking RGBT210 HMFT Precision 78.6 #19 of 19 Archive leaderboard report
Rgb-T Tracking RGBT210 HMFT Success 53.5 #19 of 19 Archive leaderboard report
Rgb-T Tracking RGBT234 HMFT Precision 78.8 #39 of 42 Archive leaderboard report
Rgb-T Tracking RGBT234 HMFT Success 56.8 #39 of 42 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections