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7 changes: 6 additions & 1 deletion README.md
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# awesome anomaly detection
# awesome anomaly detection
A curated list of awesome anomaly detection resources. Inspired by [`awesome-architecture-search`](https://github.com/sdukshis/awesome-ml) and [`awesome-automl`](https://github.com/hibayesian/awesome-automl-papers).

*Last updated: 2021/11/22*
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- MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams | **[AAAI' 20]** | [`[pdf]`](https://www.comp.nus.edu.sg/~sbhatia/assets/pdf/midas.pdf) | [`[code]`](https://github.com/bhatiasiddharth/MIDAS)
- Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network | **[NeurIPS' 20]**
- Anomaly Detection of Time Series With Smoothness-Inducing Sequential Variational Auto-Encoder | **[TNNLS' 20]**
- DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection | **[KDD' 20]** | [`[pdf]`](https://dl.acm.org/doi/10.1145/3394486.3403339) [`[promo video]`](https://youtu.be/YhfxCHBNM2g)
- Active Learning for Human-in-the-loop Customs Inspection | **[TKDE' 22]** | [`[pdf]`](https://ieeexplore.ieee.org/document/9695316) | [`[project page]`](https://ds.ibs.re.kr/bacuda/)
- Customs Fraud Detection in the Presence of Concept Drift | **[ICDMW' 21]** | [`[pdf]`](https://arxiv.org/abs/2109.14155) | [`[talk]`](https://youtu.be/1J77DJPb0gE)
- Knowledge Sharing via Domain Adaptation in Customs Fraud Detection | **[AAAI' 22]** | [`[pdf]`](http://arxiv.org/abs/2201.06759)


## Video-level anomaly detection
- Abnormal Event Detection in Videos using Spatiotemporal Autoencoder | **[ISNN' 17]** | [`[pdf]`](https://arxiv.org/pdf/1701.01546.pdf)
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