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View Code? Open in Web Editor NEWOfficial Implementation for "Mask-Attention-Free Transformer for 3D Instance Segmentation"
Official Implementation for "Mask-Attention-Free Transformer for 3D Instance Segmentation"
I observed that you utilized the pretrained weights from SSTNet during the training process. However, the SSTNet model's original input does not encompass normal information. In the context of incorporating normal information into the model, the question arises: which pretrained weights should be employed post the integration of normal information?
Can you provide more details regarding conda environment creation please?
Hi @X-Lai , Thanks for sharing this great work!
What is the purpose of attn_masks in your transformer decoder? In your paper, you mentioned that mask-attention-free-transformer.
Mask-Attention-Free-Transformer/maft/model/transformer.py
Lines 108 to 115 in 4b5048c
Thank you.
Hi,
I'm interested in potentially building on some of your code. Can you please clarify what usage license this repository is released under?
Great job! May I ask if you could provide the code for your work on the ScanNet200 and S3DIS datasets?
Hi, how can I reproduce the experimental results shown in Fig.1? I tried modifying the epoch parameter in the configs directly, but the results were significantly different. Can you assist me with this issue?
# install attention_rpe_ops
cd lib/attention_rpe_ops && python3 setup.py install && cd ../../
When I run the command, I was prompted that opt
is null.
Hi, XinLai, thank you for you great work.
Hello!
Thanks for this great job! In this paper, you have tested MAFT for ScanNetv2 and ScanNet200 with SPFormer. Have you ever tested MAFT for ScanNetv2 and ScanNet200 with Mask3D? Thanks!
Best
Dear authors,
Thanks for your job. My question is that are there any methods or repos can be referred to generate superpoints for S3DIS. And is there any plan to release the training code for S3DIS?
Best
I think your code is not complete because some modules are missing. Could you tell me when you will complete it?
In loss.py, I think a score loss is also used to train the model but it is not mentioned in the paper.
Can you provide some insight into this? I might be overlooking something...
Additionally, is there a specific reason for using the Minkowski engine as a backbone in the S3DIS dataset?"
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