Video Object Self-Annotation
Method
Method
Demonstration
Demonstration
Downloads
Downloads
Code: [Annotation Interface] [Video Mask-RCNN]
Datasets: [Accident Dataset]
Results: [ARA-Cityscapes]
If you use our code, please cite the following publications:
Publications
Publications
Trung-Nghia Le, Akihiro Sugimoto, Shintaro Ono, Hiroshi Kawasaki , "Toward Interactive Self-Annotation For Video Object Bounding Box: Recurrent Self-Learning And Hierarchical Annotation Based Framework", IEEE Winter Conference on Applications of Computer Vision , US, 2020. [PDF] [Poster] [Presentation]
License
License
Our data and code are published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. You must not use this work for commercial purposes. If you alter or build upon this work, you have to distribute the resulting work only under the same license.