Comments (3)
Hi Yonghui,
Thanks for your interest in our work.
For the distance calculation method, the two formulations ("(torch.sigmoid(nn_features_reshape + dis_bias.view(1, 1, 1, -1, 1)) - 0.5) * 2" and "(0.5-torch.sigmoid(-(nn_features_reshape + dis_bias.view(1, 1, 1, -1, 1)))) * 2") are actually equivalent as nn_features_reshape and dis_bias are both learnable embeddings.
I think it would be better if you raise your questions in this repo. I am willing to have discussions on VOS. : )
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Hi Yonghui,
Thanks for your interest in our work.
For the distance calculation method, the two formulations ("(torch.sigmoid(nn_features_reshape + dis_bias.view(1, 1, 1, -1, 1)) - 0.5) * 2" and "(0.5-torch.sigmoid(-(nn_features_reshape + dis_bias.view(1, 1, 1, -1, 1)))) * 2") are actually equivalent as nn_features_reshape and dis_bias are both learnable embeddings.
I think it would be better if you raise your questions in this repo. I am willing to have discussions on VOS. : )
I know, thanks~
In the scripts/ytb_eval_with_RPA.sh file, for the first line, the "configs.resnet101_p2t" is missing, where can i get it?
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Thanks for your correction. It should be "configs.resnet101_rpcm_ytb_stage_1"
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Related Issues (11)
- Help HOT 2
- pretrained weights for the backbone HOT 4
- About correctly loading in pretraining backbone HOT 6
- About multi-scale testing HOT 2
- 请问Reliable patch pool里面会保存所有过去帧的信息还是只保存第一帧和前一帧的信息? HOT 4
- about the reweighting operation in two modulators HOT 1
- about Shannon entropy HOT 1
- model inference HOT 1
- How Can I setup dataset and .pth path? HOT 2
- Custom testing images - empty reference labels HOT 3
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