-
related paper
|摘要|
|---|
|State-of-the-art models for semantic segmentation are based on adaptations of convolutional networks that had originally been designed for image classification. However,…
-
I am trying to run -
`scripts/extract_optical_flow.sh /temporal-segment-networks/src_folder/ /temporal-segment-networks/out_folder/ 1`
I have taken just 5 sample videos from UCF101 in my src_folder:…
-
Hi
just wanted to know your thoughts on using a Densely Connected Convolutional Networks like the one in [here](https://github.com/liuzhuang13/DenseNet) as encoder, I'm thinking of trying and impleme…
-
I have a problem ,When i try centerpoint on openpcd
python train.py --cfg_file=cfgs/kitti_models/centerpoint.yaml
Traceback (most recent call last):
File "train.py", line 230, in
main()…
-
Hello,
Thank you for such a great job and for releasing your code.
I want to train your network using a custom dataset. When I looked at the options.py file, the batch_size parameter is set to 1 a…
-
FFNs have been very successful for Google on dense volumetric EM data. Wonder if it could be adopted to brightfield.
- [ ] [Their demo inference notebook](https://github.com/google/ffn/blob/master/…
-
Hi Avanti and others,
Thank you for the great tool! I would like to use your package to compute the feature contribution for the residual network, however it seems that this type of layers is not s…
-
第194行引入的train_arcl2_cspdense_ROIpatch库中的ap_comput，但是源码中没有这个库。请问可以分享一下train_arcl2_cspdense_ROIpatch.py吗
-
1. something odd ive noticed is that the ME roundels appear not to update the network in all scenarios. smart/dense cables showing incorrect usage.
1. favoring 8 channel networks sometimes (not eno…
-
I am using the **DenseFlipOut** layer, I see that it has a mean_normal distribution over the weights and the biases by default, but I was wondering how these distributions are modified during training…
pks42 updated
10 months ago