International Conference on Computer Vision (ICCV) 2023

Towards Content-based Pixel Retrieval in Revisited Oxford and Paris Towards Content-based Pixel Retrieval in Revisited Oxford and Paris

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

Content-based Pixel Retrieval

Pixel retrieval, often referred to as segmented instance retrieval, represents an emerging area within computer vision. The primary objective is to identify pixels that represent a specific query object within a database. This involves the machine's ability to recognize, localize, and segment the query object in database images in real-time. Essentially, it's a pixel-level and instance-level recognition task, as illustrated in the figure below:

Pixel Retrieval Image

Comparison with Image Retrieval and Segmentation

Pixel retrieval can be viewed as an advanced form of image retrieval, providing insights into which specific pixels correlate with the query object. When juxtaposed with semantic and instance segmentation, pixel retrieval demands a nuanced recognition capability for targets of varying granularity. For a comprehensive understanding, please refer to our research paper.

User-Study Insights

Pixel retrieval is not just a theoretical concept; it has practical implications. Our user study indicates that pixel-level annotations during the retrieval process can notably enhance user experience. Engage with our user-study through this link.


Revisited oxford and paris datasets
example result