Figure 1. Comparisons between our approach and other single-
stage or CLIP-based approaches. (a) Previous single-stage ap-
proach, which uses a trainable ImageNet [11] pre-trained back-
bone with trainable classification and segmentation process. (b)
Previous CLIP-based approach, which is a multi-stage approach
that uses the Frozen CLIP model to produce pseudo labels and
trains an individual ImageNet pre-trained segmentation model. (c)
Our approach. Our approach is a single-stage approach that uses
a frozen CLIP model as the backbone with a trainable segmenta-
tion process, significantly reducing the training cost.