mlsanityData to 14 Oct 2026

Trajectory Prediction in Dynamic Object Tracking: A Critical Study

arXiv 2506.19341 ↗First posted 24 Jun 2025cs.CVcited by 0

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Abstract (arXiv)

This study provides a detailed analysis of current advancements in dynamic object tracking (DOT) and trajectory prediction (TP) methodologies, including their applications and challenges. It covers various approaches, such as feature-based, segmentation-based, estimation-based, and learning-based methods, evaluating their effectiveness, deployment, and limitations in real-world scenarios. The study highlights the significant impact of these technologies in automotive and autonomous vehicles, surveillance and security, healthcare, and industrial automation, contributing to safety and efficiency. Despite the progress, challenges such as improved generalization, computational efficiency, reduced data dependency, and ethical considerations still exist. The study suggests future research directions to address these challenges, emphasizing the importance of multimodal data integration, semantic information fusion, and developing context-aware systems, along with ethical and privacy-preserving frameworks.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 54 of its 145 references that are in the map. First posted on arXiv 24 Jun 2025.

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References · 54

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  5. 2018GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wildcited by 475
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38 more
  1. 2020MOTChallenge: A Benchmark for Single-Camera Multiple Target Trackingcited by 136
  2. 2020LaSOT: A High-quality Large-scale Single Object Tracking Benchmarkcited by 132
  3. 2019Audio-Visual Scene-Aware Dialogcited by 123
  4. 2016Learning to Track at 100 FPS with Deep Regression Networkscited by 89
  5. 2021MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?cited by 69
  6. 2018Learning Spatial-Temporal Regularized Correlation Filters for Visual Trackingcited by 63
  7. 2021Stepwise Goal-Driven Networks for Trajectory Predictioncited by 62
  8. 2021TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wildcited by 52
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  14. 2023MacFormer: Map-Agent Coupled Transformer for Real-time and Robust Trajectory Predictioncited by 32
  15. 2018Exploit the Connectivity: Multi-Object Tracking with TrackletNetcited by 30
  16. 2020Map-Adaptive Goal-Based Trajectory Predictioncited by 30
  17. 2022Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?cited by 29
  18. 2020Fast Template Matching and Update for Video Object Tracking and Segmentationcited by 24
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  23. 2021Dynamic Attention guided Multi-Trajectory Analysis for Single Object Trackingcited by 17
  24. 2023RSPT: Reconstruct Surroundings and Predict Trajectories for Generalizable Active Object Trackingcited by 16
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  27. 2018Tracking by Prediction: A Deep Generative Model for Mutli-Person localisation and Trackingcited by 9
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  29. 2021Multiple Object Tracking with Mixture Density Networks for Trajectory Estimationcited by 8
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  33. 2021Joint Learning Architecture for Multiple Object Tracking and Trajectory Forecastingcited by 4
  34. 2022The Stanford Drone Dataset is More Complex than We Think: An Analysis of Key Characteristicscited by 4
  35. 2017SOT for MOTcited by 3
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  38. 2022Video object tracking based on YOLOv7 and DeepSORTcited by 3

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