mlsanityData to 14 Oct 2026

SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequences

arXiv 2102.10820 ↗First posted 22 Feb 2021cs.CV cs.LG cs.ROcited by 10

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Abstract (arXiv)

Large labeled data sets are one of the essential basics of modern deep learning techniques. Therefore, there is an increasing need for tools that allow to label large amounts of data as intuitively as possible. In this paper, we introduce SALT, a tool to semi-automatically annotate RGB-D video sequences to generate 3D bounding boxes for full six Degrees of Freedom (DoF) object poses, as well as pixel-level instance segmentation masks for both RGB and depth. Besides bounding box propagation through various interpolation techniques, as well as algorithmically guided instance segmentation, our pipeline also provides built-in pre-processing functionalities to facilitate the data set creation process. By making full use of SALT, annotation time can be reduced by a factor of up to 33.95 for bounding box creation and 8.55 for RGB segmentation without compromising the quality of the automatically generated ground truth.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 13 of its 24 references that are in the map. First posted on arXiv 22 Feb 2021.

Builds on

13 of 24 references.

References · 13

  1. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
  2. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  3. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 732
  4. 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
  5. 2018The ApolloScape Open Dataset for Autonomous Driving and its Applicationcited by 190
  6. 2019The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenescited by 80
  7. 2019EasyLabel: A Semi-Automatic Pixel-wise Object Annotation Tool for Creating Robotic RGB-D Datasetscited by 58
  8. 2015Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfercited by 39
  9. 20193D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streamscited by 36
  10. 2017LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenescited by 32
  11. 2019LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Trackingcited by 20
  12. 2018Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generationcited by 12
1 more
  1. 2020YCB-M: A Multi-Camera RGB-D Dataset for Object Recognition and 6DoF Pose Estimationcited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 4; 2022: 3; 2023: 1; 2024: 1; 2025: 0; 2026: 1.

10 papers.

  1. 2023360^circ from a Single Camera: A Few-Shot Approach for LiDAR Segmentationcited by 12
  2. 2021TICaM: A Time-of-flight In-car Cabin Monitoring Datasetcited by 10
  3. 2021TIMo -- A Dataset for Indoor Building Monitoring with a Time-of-Flight Cameracited by 9
  4. 2022Baking in the Feature: Accelerating Volumetric Segmentation by Rendering Feature Mapscited by 7
  5. 2022ProgressLabeller: Visual Data Stream Annotation for Training Object-Centric 3D Perceptioncited by 6
  6. 2024Text3DAug -- Prompted Instance Augmentation for LiDAR Perceptioncited by 4
  7. 2022Semi-automatic 3D Object Keypoint Annotation and Detection for the Massescited by 1
  8. 2021DeepScanner: a Robotic System for Automated 2D Object Dataset Collection with Annotationscited by 0
  9. 20213D Annotation Of Arbitrary Objects In The Wildcited by 0
  10. 2026Adding Another Dimension to Image-based Animal Detectioncited by 0