Can I read Towards Content-based Pixel Retrieval in Revisited Oxford and Paris on EtoBox?

Towards Content-based Pixel Retrieval in Revisited Oxford and Paris by An, Guoyuan; Kim, Woo Jae; Yang, Saelyne; Li, Rong; Huo, Yuchi; Yoon, Sung-Eui is a scholarly article available to read on EtoBox.

What is Towards Content-based Pixel Retrieval in Revisited Oxford and Paris about?

This paper introduces the first two pixel retrieval benchmarks. Pixel retrieval is segmented instance retrieval. Like semantic segmentation extends classification to the pixel level, pixel retrieval is an extension of image retrieval and offers information about which pixels are related to the query object. In addition to retrieving images for the given query, it helps users quickly identify the query object in true positive images and exclude false positive images by denoting the correlated pixels. Our user study results show pixel-level annotation can significantly improve the user experience. Compared with semantic and instance segmentation, pixel retrieval requires a fine-grained recognition capability for variable-granularity targets. To this end, we propose pixel retrieval benchmarks named PROxford and PRParis, which are based on the widely used image retrieval datasets, ROxford and RParis. Three professional annotators label 5,942 images with two rounds of double-checking and refinement. Furthermore, we conduct extensive experiments and analysis on the SOTA methods in image search, image matching, detection, segmentation, and dense matching using our pixel retrieval benchmar

Author

An, Guoyuan; Kim, Woo Jae; Yang, Saelyne; Li, Rong; Huo, Yuchi; Yoon, Sung-Eui

Published

2023

Language

EN