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LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking

arXiv 1809.07845 ↗First posted 20 Sep 2018cs.CVcited by 424

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Abstract (arXiv)

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 evaluation of tracking algorithms. Moreover, considering the close connections of visual appearance and natural language, we enrich LaSOT by providing additional language specification, aiming at encouraging the exploration of natural linguistic feature for tracking. A thorough experimental evaluation of 35 tracking algorithms on LaSOT is presented with detailed analysis, and the results demonstrate that there is still a big room for improvements.

Key facts. Cited by 424 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Sep 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 72; 2022: 55; 2023: 72; 2024: 88; 2025: 76; 2026: 61.

424 papers.

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  1. 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,530
  2. 2021Transformer Trackingcited by 412
  3. 2021Learning Spatio-Temporal Transformer for Visual Trackingcited by 348
  4. 2022Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Frameworkcited by 328
  5. 2022MixFormer: End-to-End Tracking with Iterative Mixed Attentioncited by 278
  6. 2023PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Trackingcited by 274
  7. 2021Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Trackingcited by 220
  8. 2023Video Understanding with Large Language Models: A Surveycited by 203
  9. 2023Universal Instance Perception as Object Discovery and Retrievalcited by 190
  10. 2023Visual Prompt Multi-Modal Trackingcited by 141
  11. 2022AiATrack: Attention in Attention for Transformer Visual Trackingcited by 137
  12. 2021Learning Target Candidate Association to Keep Track of What Not to Trackcited by 131
38 more
  1. 2024ODTrack: Online Dense Temporal Token Learning for Visual Trackingcited by 129
  2. 2021SwinTrack: A Simple and Strong Baseline for Transformer Trackingcited by 126
  3. 2021Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmarkcited by 124
  4. 2022Transforming Model Prediction for Trackingcited by 117
  5. 2022Revealing the Dark Secrets of Masked Image Modelingcited by 117
  6. 2021LasHeR: A Large-scale High-diversity Benchmark for RGBT Trackingcited by 94
  7. 2022Towards Grand Unification of Object Trackingcited by 93
  8. 2023Generalized Relation Modeling for Transformer Trackingcited by 93
  9. 2021STMTrack: Template-free Visual Tracking with Space-time Memory Networkscited by 91
  10. 2024SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memorycited by 91
  11. 2021LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Searchcited by 82
  12. 2023Robust Object Modeling for Visual Trackingcited by 80
  13. 2024SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Treecited by 77
  14. 2022LVOS: A Benchmark for Long-term Video Object Segmentationcited by 76
  15. 2024Autoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformerscited by 76
  16. 2022Transformer Tracking with Cyclic Shifting Window Attentioncited by 75
  17. 2023HIPTrack: Visual Tracking with Historical Promptscited by 71
  18. 2025StreamForest: Efficient Online Video Understanding with Persistent Event Memorycited by 71
  19. 2024Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performancecited by 70
  20. 2022TCTrack: Temporal Contexts for Aerial Trackingcited by 69
  21. 2021Learn to Match: Automatic Matching Network Design for Visual Trackingcited by 67
  22. 2021DepthTrack : Unveiling the Power of RGBD Trackingcited by 66
  23. 2022BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Videocited by 66
  24. 2023Single-Model and Any-Modality for Video Object Trackingcited by 64
  25. 2024OneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuningcited by 64
  26. 2024A Distractor-Aware Memory for Visual Object Tracking with SAM2cited by 63
  27. 2021Do Different Tracking Tasks Require Different Appearance Models?cited by 62
  28. 2022Correlation-Aware Deep Trackingcited by 62
  29. 2023Towards Unified Token Learning for Vision-Language Trackingcited by 62
  30. 2023Joint Visual Grounding and Tracking with Natural Language Specificationcited by 59
  31. 2025MOSEv2: A More Challenging Dataset for Video Object Segmentation in Complex Scenescited by 59
  32. 2022Prompting for Multi-Modal Trackingcited by 58
  33. 2024Online Video Understanding: OVBench and VideoChat-Onlinecited by 58
  34. 2023MixFormerV2: Efficient Fully Transformer Trackingcited by 56
  35. 2023Exploring Lightweight Hierarchical Vision Transformers for Efficient Visual Trackingcited by 53
  36. 2023Compact Transformer Tracker with Correlative Masked Modelingcited by 50
  37. 2024Explicit Visual Prompts for Visual Object Trackingcited by 50
  38. 2024Vitron: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editingcited by 49

50 most cited of 424 All 424 (JSON)