Generative Region-Language Pretraining for Open-Ended Object Detection

Understand

In recent research, significant attention has been devoted to the open-vocabulary object detection task, aiming to generalize beyond the limited number of classes labeled during training and detect objects described by arbitrary category names at inference.

• Compared with conventional object detection, open vocabulary object detection largely extends the object detection categories.
• However, it relies on calculating the similarity between image regions and a set of arbitrary category names with a pretrained vision-and-language model.
• This implies that, despite its open-set nature, the task still needs the predefined object categories during the inference stage.