mlsanityData to 7 Oct 2026

TIMo -- A Dataset for Indoor Building Monitoring with a Time-of-Flight Camera

arXiv 2108.12196 ↗First posted 27 Aug 2021cs.CVcited by 9

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Abstract (arXiv)

We present TIMo (Time-of-flight Indoor Monitoring), a dataset for video-based monitoring of indoor spaces captured using a time-of-flight (ToF) camera. The resulting depth videos feature people performing a set of different predefined actions, for which we provide detailed annotations. Person detection for people counting and anomaly detection are the two targeted applications. Most existing surveillance video datasets provide either grayscale or RGB videos. Depth information, on the other hand, is still a rarity in this class of datasets in spite of being popular and much more common in other research fields within computer vision. Our dataset addresses this gap in the landscape of surveillance video datasets. The recordings took place at two different locations with the ToF camera set up either in a top-down or a tilted perspective on the scene. The dataset is publicly available at https://vizta-tof.kl.dfki.de/timo-dataset-overview/.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 20 of its 47 references that are in the map. First posted on arXiv 27 Aug 2021.

Builds on

20 of 47 references.

References · 20

  1. 2017Mask R-CNNcited by 7,259
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8 more
  1. 2019Multi-timescale Trajectory Prediction for Abnormal Human Activity Detectioncited by 59
  2. 2018An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videoscited by 45
  3. 2020Driver Anomaly Detection: A Dataset and Contrastive Learning Approachcited by 41
  4. 2017RGB-D-based Human Motion Recognition with Deep Learning: A Surveycited by 37
  5. 2016RGBD Datasets: Past, Present and Futurecited by 11
  6. 2021SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequencescited by 10
  7. 2021TICaM: A Time-of-flight In-car Cabin Monitoring Datasetcited by 10
  8. 2017Large-scale Isolated Gesture Recognition Using Convolutional Neural Networkscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 0; 2025: 4; 2026: 1.

9 papers.

  1. 2022A Survey on Infrared Image and Video Setscited by 7
  2. 2022Unsupervised Anomaly Detection from Time-of-Flight Depth Imagescited by 6
  3. 2025iSafetyBench: A video-language benchmark for safety in industrial environmentcited by 5
  4. 2025RICO: Two Realistic Benchmarks and an In-Depth Analysis for Incremental Learning in Object Detectioncited by 5
  5. 2025Incremental Object Detection with Prompt-based Methodscited by 2
  6. 2023Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encodercited by 1
  7. 2025HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detectioncited by 1
  8. 2026MULTI: Disentangling Camera Lens, Sensor, View, and Domain for Novel Image Generationcited by 1
  9. 2023Achieving RGB-D level Segmentation Performance from a Single ToF Cameracited by 0