IIIT-Seed (Semantic Edges) dataset contains 500 RGBD images of varying complexity. This dataset consists of objects such as tables, chairs, cupboard shelves, boxes and household objects in addition to walls and floors. This dataset is reported in the paper cited below :
Nishit Soni, Anoop M. Namboodiri, CV Jawahar and Srikumar Ramalingam. Semantic Classification of Boundaries of an RGBD Image. In Proceedings of the British Machine Vision Conference (BMVC 2015), pages 114.1-114.12. BMVA Press, September 2015. [paper] [abstract] [poster] [code] [bibtex]
- Download the dataset : here. Cite our paper if you use this dataset. [bibtex].
- Test and train files : test split and train split.
- Download 100 images of NYU dataset used to test our approach on: here.
- Pb edge links for our dataset as well as the NYU dataset : here.
- Groundtruth for both the datasets : here.