Open Vocabulary Image Segmentation

Open-vocabulary image segmentation aims to automatically partition images into regions corresponding to arbitrary text descriptions, going beyond predefined object categories. Current research focuses on developing efficient methods for classifying these regions, often leveraging pre-trained vision-language models like CLIP and incorporating hierarchical representations to handle varying levels of granularity in visual scenes. These advancements are improving the accuracy and scalability of image segmentation, with implications for applications ranging from improved image search and retrieval to more robust scene understanding in robotics and autonomous systems.