Iclr 2024 Object Detection

Iclr 2024 Object Detection. In this paper, we suggest that the failure of knowledge distillation on object detection is mainly caused by two reasons: Through extensive experiments in object detection, classification, and adversarial example generation across $5$ datasets and $12$ model architectures, we demonstrate that the.

Extensive experiments on the coco benchmark. The learned positive prompt (for all classes) and negative prompts (for each class) are leveraged to measure the.