Comments (3)
Thanks for your interest.
You can double-check it. In fact, the overall performance is already provided. Our final performance is determined using the semantic alignment results from the last layer of the Decoder. As shown below.
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Thanks for your great response. I find the performance for each head is 0. Do you konw why this happens?
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I apologize for forgetting to comment out these two lines. L174 - L175
# note only consider the last layer
if prefix != 'last_':
continue
I only kept the evaluation output of the last layer. Actually, you only need to refer to the results from this layer.
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Related Issues (13)
- when will the code be released? HOT 1
- Data processing for VG-w/o-ON HOT 1
- Problem of Text-Decoupling. HOT 1
- What dose “choices” and “new_pts” mean? HOT 1
- problem of evaluation HOT 1
- Overfitting when training with 2 GPUs HOT 2
- Question of visualization HOT 2
- Problem of learning rate HOT 1
- I am confused about the log.txt file HOT 2
- group_free_pred_bboxes HOT 1
- The pretrained PointNet++ backbone HOT 2
- should we add `self.text_encoder.eval()` ? HOT 2
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