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Pre-trained POMP Prompt

Name (configs) Model ImageNet-21K Acc. Cross-dataset Acc. Cross-domain Acc. Epochs Prompt Length
vit_b16_ep5_randaug2_unc1000_16shots_nctx4_cscFalse_ctpend_seed42.pth.tar link 24.9 66.7 60.4 5 4
vit_b16_ep20_randaug2_unc1000_16shots_nctx16_cscFalse_ctpend_seed42.pth.tar link 25.2 65.1 60.0 20 16

make a pretrained/ directory under the main directory prompt-pretraining/ and then download the above checkpoints to the pretrained directory. The directory structure should look like:

prompt-pretraining/
|–– pretrained/
|   |–– vit_b16_ep5_randaug2_unc1000_16shots_nctx4_cscFalse_ctpend_seed42.pth.tar
|   |–– vit_b16_ep20_randaug2_unc1000_16shots_nctx16_cscFalse_ctpend_seed42.pth.tar

Note that the ckpt is only a few KBs since it only contains the pretrained prompt, which is an embedding tensor with size of 4x512 (or 16x512).

POMP for object detection (based on Detic)

(1) Open-vocabulary LVIS

Name (configs) Model mAPr mAP Prompt Legth
Detic_LbaseI_CLIP_R5021k_640b64_4x_ft4x_max-size_pomp.pth link 25.2 32.7 16

(2) Cross-dataset

Name (configs) Model AP50 on LVIS (source) AP50 on COCO (target) AP50 on Object365 (target) Prompt Legth
Detic_LI_CLIP_R5021k_640b64_4x_ft4x_max-size_pomp.pth link 50.7 58.0 23.4 16

POMP for semantic segmentation (based on ZSSeg)

(1) Open-vocabulary COCO Stuff

Name (configs) Model hIoU mIoU-unseen Prompt Legth
coco-stuff-164k-156_zero_shot_proposal_classification_learn_prompt_pomp_bs32_10k.pth link 39.1 38.2 16
coco-stuff-164k-156_zero_shot_maskformer_R101c_pomp_tuned_bs32_60k.pth link 39.1 38.2 16

(2) Open-vocabulary Pascal VOC

Name (configs) Model hIoU mIoU-unseen Prompt Legth
voc-11k-15_zero_shot_proposal_classification_learn_prompt_pomp_bs16_10k.pth link 84.4 76.8 16
voc-11k-15_zero_shot_maskformer_R101c_pomp_tuned_bs16_20k.pth link 84.4 76.8 16

(3) Cross-dataset

Name (configs) Model mIoU on COCO Stuff (source) mIoU on ADE20K (target) mIoU on PASCAL Context (target) Prompt Legth
coco-stuff-164k-171_zero_shot_maskformer_R101c_pomp_tuned_bs32_60k.pth link 41.1 20.7 51.1 16