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Hi thanks for your excellent work.
May I ask what's your evaluation result of the VoteNet?
I am reproducing BoxNet (the simple version of VoteNet) by Pytorch and the result is far from the BoxNet c…
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Dear authors,
I tried to evaluate ScanNet-pretrained model you provided as illustrated in REANDME and I got 57.3156 mAP@0.25 and 34.0198 mAP@0.5, but according to issue #11 this result is obvious …
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Hi!
Most of the code uses mat/pickle files present in the `metadata/sunrgbd/` folder as ground truth. A few examples of the files being used are:
- `metadata/sunrgbd/Dataset/data_clean/data_all…
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The orignal dataset claims they have much more than the ~5000 images here.
Is this repo missing anything?
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Hi, Siyuan
When I train the bdbnet from scratch by
`sh scripts/sunrgbd_train_bdbnet.sh`, it reminded me that
![image](https://user-images.githubusercontent.com/23393128/55378672-847a6500-554c-11e9…
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You have some hard-coded path in the pickle files, e.g., in this line: https://github.com/thusiyuan/cooperative_scene_parsing/blob/master/preprocess/sunrgbd/sunrgbd_parser.py#L116
img_info['imgrgb…
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Link of raw data of sunrgbd has broken. Is the raw data of sunrgbd downloaded from the http://rgbd.cs.princeton.edu/challenge.html?
Thank the great work you have done!
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你好,看到你上传的代码,太开心了,请问有没有相关的结果可以看下?我有个需求是对16线的雷达点进行场景障碍物识别,请问这种方法对稀疏点云是否会奏效呢?您有什么好的建议,请指教,谢谢。
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Hey, thank you for your support on this code so far! Do you mind sharing the SUNCG preprocessed data or the code to preprocess the dataset? It will be super helpful if you can release it in the same w…
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Hi, thank you for the great work! It seems that two download links for the preprocessed SUNRGBD dataset and GT in this github repo are the same. What's the correct download link for the dataset?