LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking
Temple University · Temple College · +1 more institution
Abstract
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 in these sequences is carefully and manually annotated with a bounding box, making LaSOT the largest, to the best of our knowledge, densely annotated tracking benchmark. The average video length of LaSOT is more than 2,500 frames, and each sequence comprises various challenges deriving from the wild where target objects may disappear and re-appear again in the view. By releasing LaSOT, we expect to provide the community with a large-scale dedicated benchmark with high quality for both the training of deep trackers and the veritable…
Citation impact
- FWCI
- 68.48
- Percentile
- 100%
- References
- 78
Authors
10Topics & keywords
- Benchmark (surveying)
- Computer science
- Minimum bounding box
- Tracking (education)
- Video tracking
- BitTorrent tracker
- Artificial intelligence
- Frame (networking)
- Quality Education