Vast Vocabulary Visual Detection

Vast vocabulary visual detection (VVD) focuses on developing computer vision systems capable of identifying and locating a significantly large number of object categories within images and videos, going beyond the limitations of existing datasets. Current research emphasizes improving model architectures and training strategies to handle the complexities of vast category sets, including exploring hierarchical category structures and leveraging knowledge distillation from vision-language models to enhance object recognition accuracy across diverse domains. The development of large-scale datasets like V3Det, with its extensive vocabulary and hierarchical annotations, is crucial for benchmarking and driving progress in this field, ultimately leading to more robust and versatile object detection systems for various applications.