mlsanityData to 14 Oct 2026

TAPL: Dynamic Part-based Visual Tracking via Attention-guided Part Localization

arXiv 2110.13027 ↗First posted 25 Oct 2021cs.CVcited by 0

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Abstract (arXiv)

Holistic object representation-based trackers suffer from performance drop under large appearance change such as deformation and occlusion. In this work, we propose a dynamic part-based tracker and constantly update the target part representation to adapt to object appearance change. Moreover, we design an attention-guided part localization network to directly predict the target part locations, and determine the final bounding box with the distribution of target parts. Our proposed tracker achieves promising results on various benchmarks: VOT2018, OTB100 and GOT-10k

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 31 of its 43 references that are in the map. First posted on arXiv 25 Oct 2021.

Builds on

31 of 43 references.

References · 31

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2020End-to-End Object Detection with Transformerscited by 7,414
  4. 2016Categorical Reparameterization with Gumbel-Softmaxcited by 2,739
  5. 2016Fully-Convolutional Siamese Networks for Object Trackingcited by 568
  6. 2018GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wildcited by 475
  7. 2018SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networkscited by 446
  8. 2018LaSOT: A High-quality Benchmark for Large-scale Single Object Trackingcited by 429
  9. 2018YouTube-VOS: A Large-Scale Video Object Segmentation Benchmarkcited by 383
  10. 2021Learning Spatio-Temporal Transformer for Visual Trackingcited by 350
  11. 2019Learning Discriminative Model Prediction for Trackingcited by 344
  12. 2018ATOM: Accurate Tracking by Overlap Maximizationcited by 285
19 more
  1. 2020Probabilistic Regression for Visual Trackingcited by 231
  2. 2021Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Trackingcited by 220
  3. 2020Ocean: Object-aware Anchor-free Trackingcited by 212
  4. 2020Siamese Box Adaptive Network for Visual Trackingcited by 189
  5. 2018Distractor-aware Siamese Networks for Visual Object Trackingcited by 187
  6. 2019SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelinescited by 177
  7. 2019Siam R-CNN: Visual Tracking by Re-Detectioncited by 174
  8. 2019SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Trackingcited by 148
  9. 2020Know Your Surroundings: Exploiting Scene Information for Object Trackingcited by 119
  10. 2020Deformable Siamese Attention Networks for Visual Object Trackingcited by 97
  11. 2020Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimationcited by 81
  12. 2019Learning the Model Update for Siamese Trackerscited by 76
  13. 2019D3S -- A Discriminative Single Shot Segmentation Trackercited by 69
  14. 2018Learning Dynamic Memory Networks for Object Trackingcited by 59
  15. 2019GradNet: Gradient-Guided Network for Visual Object Trackingcited by 41
  16. 2020RPT: Learning Point Set Representation for Siamese Visual Trackingcited by 26
  17. 2017End-to-end Flow Correlation Tracking with Spatial-temporal Attentioncited by 21
  18. 2021Learning to Filter: Siamese Relation Network for Robust Trackingcited by 15
  19. 2019Discriminative and Robust Online Learning for Siamese Visual Trackingcited by 10

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