I will be presenting our work on adversarial robustness at ICML'19 and CVPR'19 in Long Beach beginning next week!


Jianbing Shen, Xiaopeng Hao, Zhiyuan Liang, Yu Liu, Wenguan Wang, Ling Shao. Real-Time Superpixel Segmentation by DBSCAN Clustering Algorithm. TIP, 2016.

Shen et al. introduce a DBSCAN based algorithm for superpixel segmentation. The proposed algorithm consists of two steps: First, an initial superpixel segmentation is found using a spatially-restricted DBSCAN algorithm. Essentially, DBSCAN is augmented by a local search strategy. Second, the initial superpixels – which may be very small in regions with high color variation – are refined. To this end, superpixels whose size does into exceed a specific threshold are merged into the “closest” neighboring superpixels. This is repeated until all superpixel exceed the threshold. The results superpixels are illustrated in Figure 1 in comparison to other superpixel algorithms.

Figure 1: Qualitative results, from top to bottom: SLIC, LSC, ERS and DBSCAN.

What is your opinion on the summarized work? Or do you know related work that is of interest? Let me know your thoughts in the comments below: