The paper presents RegionSpot, a novel region recognition architecture for open-world object detection. It builds on vision-language (ViL) foundation models like CLIP, and addresses challenges such as intensive training requirements, data noise, and lack of contextual information. RegionSpot integrates localization knowledge from a localization foundation model with semantic information extracted from a ViL model. The paper demonstrates that RegionSpot significantly outperforms previous models, offering computational savings and improved performance in object recognition.
Publication date: 3 Nov 2023
Project Page: https://github.com/Surrey-UPLab/Recognize-Any-Regions
Paper: https://arxiv.org/pdf/2311.01373
