Comments (5)
vealocia
commented on August 16, 2024
1
All losses l_cls, l_box, l_mask are added to every stage to achieve deep supervision.
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Yuxin-CV
commented on August 16, 2024
1
Thank you!
Do you attach a loss to every stage of mask processing? Or only to the last stage?
All DETR-like systems need deep supervision in their decoder.
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vealocia
commented on August 16, 2024
Hi, @vadimkantorov ! Thanks for your interest in our Work.
object_feats is exact the q_{t-1} and q_t.
q_0 is stored in EmbeddingRPNHead.
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vadimkantorov
commented on August 16, 2024
Thank you!
Do you attach a loss to every stage of mask processing? Or only to the last stage?
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vadimkantorov
commented on August 16, 2024
Thanks for clarifications!
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Related Issues (20)
- pytorch2onnx failed HOT 1
- AttributeError: 'EmbeddingRPNHead' object has no attribute 'async_simple_test_rpn' HOT 2
- mAP = 0 all the time HOT 7
- Details about QueryTrack HOT 5
- which learning rate is true? HOT 2
- The parameter of the tracking loss HOT 2
- gpu HOT 2
- how to inference the pretrained model on my test data without GT HOT 1
- KeyError: "QueryInst: 'QueryRoIHead is not in the models registry'" HOT 1
- Base config file does not exist
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- 您好，请问代码里是不是没使用预训练模型？ HOT 1
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- Loss value when training QueryInst
- test stage mAP(box)=0, mAP(seg)=0.71 HOT 1
- Welcome update to OpenMMLab 2.0
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