Awesome-Trajectory-Similarity

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Awesome-Trajectory-Similarity

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A professional list on deep learning models for Trajectory Similarity Measurement and Trajectory Distance Computation

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# Deep Trajectory Similarity Measurement and Trajectory Distance Computation

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:star2: A professional list on deep learning models for Trajectory Similarity Measurement and Trajectory Distance Computation

:pencil2: We will continue to update this list with the newest resources. If you find any missed resources (paper/code) or errors, please feel free to open an issue or make a pull request.

:rocket: For a collection of general deep learning-basd trajectory data management and mining papers, please check [this repo](https://github.com/yoshall/Awesome-Trajectory-Computing).

## Survey
* A Survey of Trajectory Distance Measures and Performance Evaluation, in *VLDBJ* 2020. [\[paper\]](https://zheng-kai.com/paper/vldbj_2019.pdf)
* A Comparative Analysis of Trajectory Similarity Measures, in *GIScience & Remote Sensing* 2021. [\[paper\]](https://www.tandfonline.com/doi/pdf/10.1080/15481603.2021.1908927)
* Spatio-Temporal Trajectory Similarity Measures: A Comprehensive Survey and Quantitative Study, in *TKDE* 2023. [\[paper\]](https://arxiv.org/pdf/2303.05012.pdf) [\[code\]](https://github.com/ZJU-DAILY/TSM)
* Trajectory Similarity Measurement: An Efficiency Perspective, in *arXiv* 2023. [\[paper\]](https://arxiv.org/pdf/2311.00960.pdf) [\[code\]](https://github.com/changyanchuan/traj-simi-efficiency)

## Deep Learning-based Methods

### Free Space

##### 2018
* Deep Representation Learning for Trajectory Similarity Computation, in *ICDE* 2018. [\[paper\]](https://xiucheng.org/assets/pdfs/icde18-t2vec.pdf) [\[code\]](https://github.com/boathit/t2vec)
  
##### 2019
* Computing Trajectory Similarity in Linear Time: A Generic Seed-Guided Neural Netric Learning Approach, in *ICDE* 2019. [\[paper\]](http://yaodi.info:5002/papers/icde19.pdf) [\[code\]](https://github.com/yaodi833/NeuTraj)
* Effective and Efficient Sports Play Retrieval with Deep Representation Learning, in *KDD* 2019. [\[paper\]](https://zhengwang125.github.io/paper/play2vec.pdf) [\[code\]](https://github.com/zhengwang125/play2vec)

##### 2020
* Trajectory Similarity Learning with Auxiliary Supervision and Optimal Matching, in *IJCAI* 2020. [\[paper\]](https://www.ijcai.org/proceedings/2020/0444.pdf)
* Representation Learning with Multi-Level Attention for Activity Trajectory Similarity Computation, in *TKDE* 2020. [\[paper\]](https://repository.kaust.edu.sa/server/api/core/bitstreams/26d2e51b-bc0f-46f7-b191-e403bc3f6822/content)

##### 2021
* T3S: Effective Representation Learning for Trajectory Similarity Computation, in *ICDE* 2021. [\[paper\]](https://ieeexplore.ieee.org/document/9458934)
* Similar Trajectory Search with Spatio-Temporal Deep Representation Learning, in *TIST* 2021. [\[paper\]](https://dl.acm.org/doi/10.1145/3466687)
* On Accurate Computation of Trajectory Similarity via Single Image Super-Resolution, in *IJCNN* 2021. [\[paper\]](https://www.researchgate.net/profile/Fei-Wang-144/publication/354716428_On_Accurate_Computation_of_Trajectory_Similarity_via_Single_Image_Super-Resolution/links/622f300ba39db062db9ca2e6/On-Accurate-Computation-of-Trajectory-Similarity-via-Single-Image-Super-Resolution.pdf) [\[code\]](https://github.com/C-Harlin/trjsr)
* Embedding-based Similarity Computation for Massive Vehicle Trajectory Data, in *IoTJ* 2021. [\[paper\]](https://ieeexplore.ieee.org/abstract/document/9521568)

##### 2022
* TMN: Trajectory Matching Networks for Predicting Similarity, in *ICDE* 2022. [\[paper\]](https://ieeexplore.ieee.org/document/9835456) [\[code\]](https://github.com/PeilunYang/TMN)
* TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation, in *KDD* 2022. [\[paper\]](https://dl.acm.org/doi/pdf/10.1145/3534678.3539358) [\[code\]](https://github.com/HuHaonan-CHN/TrajGAT)
* Efficient Trajectory Similarity Computation with Contrastive Learning, in *CIKM* 2022. [\[paper\]](https://zheng-kai.com/paper/cikm_2022_deng.pdf) [\[code\]](https://github.com/LIWEIDENG0830/CL-TSim)
* CSTRM: Contrastive Self-Supervised Trajectory Representation Model for Trajectory Similarity Computation, in *CC* 2022. [\[paper\]](https://www.sciencedirect.com/science/article/abs/pii/S0140366422000019)
  
##### 2023
* Trajectory Similarity Learning with Dual-Feature Attention, in *ICDE* 2023. [\[paper\]](https://people.eng.unimelb.edu.au/jianzhongq/papers/ICDE2023_TrajCL.pdf) [\[code\]](https://github.com/changyanchuan/TrajCL)
* Towards Robust Trajectory Similarity Computation: Representation-based Spatio-Temporal Similarity Quantification, in *WWWJ* 2023. [\[paper\]](https://link.springer.com/article/10.1007/s11280-022-01085-4) [\[code\]](https://github.com/Like-China/TrajectorySim-RSTS-model)
* Self-Supervised Contrastive Representation Learning for Large-Scale Trajectories, in *Future Generation Computer Systems* 2023. [\[paper\]](https://www.sciencedirect.com/science/article/abs/pii/S0167739X23002376)

##### 2024
* KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding, in *AAAI* 2024 [\[paper\]](https://ojs.aaai.org/index.php/AAAI/article/view/28672/29305)

### Road Network

##### 2020
* Trembr: Exploring Road Networks for Trajectory Representation Learning, in *TIST* 2020. [\[paper\]](https://dl.acm.org/doi/pdf/10.1145/3361741)

##### 2021
* A Graph-based Approach for Trajectory Similarity Computation in Spatial Networks, in *KDD* 2021. [\[paper\]](https://dl.acm.org/doi/pdf/10.1145/3447548.3467337)

##### 2022
* Spatio-Temporal Trajectory Similarity Learning in Road Networks, in *KDD* 2022. [\[paper\]](https://arxiv.org/pdf/2112.09339.pdf) [\[code\]](https://github.com/zealscott/ST2Vec)

##### 2023
* LightPath: Lightweight and Scalable Path Representation Learning, in *KDD* 2023. [\[paper\]](https://dl.acm.org/doi/pdf/10.1145/3580305.3599415)
* GRLSTM: Trajectory Similarity Computation with Graph-based Residual LSTM, in *AAAI* 2023. [\[paper\]](https://ojs.aaai.org/index.php/AAAI/article/view/25624/25396) [\[code\]](https://github.com/slzhou-xy/GRLSTM)
* Spatial Structure-Aware Road Network Embedding via Graph Contrastive Learning, in *EDBT* 2023. [\[paper\]](https://people.eng.unimelb.edu.au/jianzhongq/papers/EDBT2023_RoadNetworkEmbedding.pdf) [\[code\]](https://github.com/changyanchuan/SARN)

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