# Integrated Object Detection and Tracking with Tracklet-Conditioned Detection

arXiv: https://arxiv.org/abs/1811.11167 · HTML: https://mlsanity.com/paper/1811.11167/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Nov 2018.

## Built on by (most cited first, 17 of 17)

- [ByteTrack: Multi-Object Tracking by Associating Every Detection Box](https://mlsanity.com/paper/2110.06864/) (2021)
- [Track to Detect and Segment: An Online Multi-Object Tracker](https://mlsanity.com/paper/2103.08808/) (2021)
- [Video K-Net: A Simple, Strong, and Unified Baseline for Video Segmentation](https://mlsanity.com/paper/2204.04656/) (2022)
- [RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation](https://mlsanity.com/paper/2105.04322/) (2021)
- [Keypoint-Based Category-Level Object Pose Tracking from an RGB Sequence with Uncertainty Estimation](https://mlsanity.com/paper/2205.11047/) (2022)
- [YOLOV: Making Still Image Object Detectors Great at Video Object Detection](https://mlsanity.com/paper/2208.09686/) (2022)
- [CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking](https://mlsanity.com/paper/2107.05150/) (2021)
- [Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detection](https://mlsanity.com/paper/2212.10147/) (2022)
- [SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes](https://mlsanity.com/paper/2211.07173/) (2022)
- [Practical Video Object Detection via Feature Selection and Aggregation](https://mlsanity.com/paper/2407.19650/) (2024)
- [Multi-resolution Rescored ByteTrack for Video Object Detection on Ultra-low-power Embedded Systems](https://mlsanity.com/paper/2404.11488/) (2024)
- [Multi-object Tracking with a Hierarchical Single-branch Network](https://mlsanity.com/paper/2101.01984/) (2021)
- [VariabilityTrack:Multi-Object Tracking with Variable Speed Object Movement](https://mlsanity.com/paper/2203.06424/) (2022)
- [A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning](https://mlsanity.com/paper/2205.02371/) (2022)
- [D^bf3: Duplicate Detection Decontaminator for Multi-Athlete Tracking in Sports Videos](https://mlsanity.com/paper/2209.12248/) (2022)
- [Object Permanence in Object Detection Leveraging Temporal Priors at Inference Time](https://mlsanity.com/paper/2211.15505/) (2022)
- [MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes](https://mlsanity.com/paper/2605.15423/) (2026)

## Abstract (arXiv)

Accurate detection and tracking of objects is vital for effective video understanding. In previous work, the two tasks have been combined in a way that tracking is based heavily on detection, but the detection benefits marginally from the tracking. To increase synergy, we propose to more tightly integrate the tasks by conditioning the object detection in the current frame on tracklets computed in prior frames. With this approach, the object detection results not only have high detection responses, but also improved coherence with the existing tracklets. This greater coherence leads to estimated object trajectories that are smoother and more stable than the jittered paths obtained without tracklet-conditioned detection. Over extensive experiments, this approach is shown to achieve state-of-the-art performance in terms of both detection and tracking accuracy, as well as noticeable improvements in tracking stability.