Interactive Labeling Algorithm is a very interesting research field, which aims to help annotate large-scale datasets with less effort for computer vision community. The annotator iteratively provides corrective annotations for the current machine annotations.

This is a collection of research papers of Interactive Labeling Algorithm. The papers are sorted by time. Any suggestions and pull requests are welcome.

The sharing principle of these references here is for research. If any authors do not want their paper to be listed here, please feel free to contact Kaiwen Zha (Email: kaiwenzha [AT] gmail.com).

• Popular Annotation Tools
• Interactive Segmentation Algorithms
  • Optimization Methods
  • Geodesic Methods
  • FCN-Based Semantic Segmentation Methods
  • Vertex Prediction Methods
  • Full Image Segmentation Methods
  • Others
• Interactive Bounding-box Labeling Algorithms
• Interactive Active Learning via Relative Attributes
• Other Interesting Explorations

• LabelMe: a database and web-based tool for image annotation by Russell et al. IJCV 2008
• Efficiently Scaling Up Crowdsourced Video Annotation by Vondrick et al. IJCV 2012
• Microsoft COCO: Common Objects in Context by Lin et al. ECCV 2014
• BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling by Yu et al. arXiv 2018

• Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images by Boykov et al. ICCV 2001
• Grabcut: Interactive foreground extraction using iterated graph cuts by Rother et al. SIGGRAPH 2004
• Densecut: Densely connected crfs for realtime grabcut by Cheng et al. CGF 2015
• Deep extreme cut: From extreme points to object segmentation by Maninis et al. CVPR 2018

• Geodesic matting: A framework for fast interactive image and video segmentation and matting by Bai et al. IJCV 2009
• Geodesic image and video editing by Criminisi et al. TOG 2010
• Geodesic star convexity for interactive image segmentation by Gulshan et al. CVPR 2010

• Deep interactive object selection by Xu et al. CVPR 2016
• Regional interactive image segmentation networks by Liew et al. ICCV 2017
• Interactive boundary prediction for object selection by Le et al. ECCV 2018
• Interactive image segmentation with latent diversity by Li et al. CVPR 2018
• Iteratively trained interactive segmentation by Mahadevan et al. BMVC 2018
• A fully convolutional two-stream fusion network for interactive image segmentation by Hu et al. Neural Networks 2019

• Annotating Object Instances with a Polygon-RNN by Castrejon et al. CVPR 2017
• Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++ by Acuna et al. CVPR 2018

• Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation by Andriluka et al. ACM MM 2018
• Interactive Full Image Segmentation by Agustsson et al. arXiv 2018

• Random walks for image segmentation by Grady et al. TPAMI 2006
• Predicting sufficient annotation strength for interactive foreground segmentation by Jain et al. ICCV 2013
• Video segmentation with just a few strokes by Nagaraja et al. ICCV 2015

• Training object class detectors from eye tracking data by Papadopoulos et al. ECCV 2014
• We don’t need no bounding-boxes: Training object class detectors using only human verification by Papadopoulos et al. CVPR 2016
• Extreme clicking for efficient object annotation by Papadopoulos et al. ICCV 2017
• Training object class detectors with click supervision by Papadopoulos et al. CVPR 2017
• Learning intelligent dialogs for bounding box annotation by Konyushkova et al. CVPR 2018

• Visual recognition with humans in the loop by Branson et al. ECCV 2010
• Relative attributes by Parikh et al. ICCV 2011
• Attributes for classifier feedback by Parkash et al. ECCV 2012
• Simultaneous active learning of classifiers & attributes via relative feedback by Biswas et al. CVPR 2013
• Similarity comparisons for interactive finegrained categorization by Wah et al. CVPR 2014

• What’s it going to cost you?: Predicting effort vs. informativeness for multilabel image annotations by Vijayanarasimhan et al. CVPR 2009
• Active annotation translation by Branson et al. CVPR 2014
• Best of both worlds: human-machine collaboration for object annotation by Russakovsky et al. CVPR 2015
• Guide me: Interacting with deep networks by Rupprecht et al. CVPR 2018