yinjunbo

@zxy-HIT @ChenGQ26 Hi！Could you please tell me have you succeed in training?

@xue1liu2 Try to open the terminal in the home directory of the master, and input : python -m src.flownet2.train according to README.

@junfanlin HELLO! I met the same problem as you. It seems that, the model can only learn the background information with the augmentation process . The LOSS of flownet_s is...

Will `np.concatenate(sweep_points_list, axis=0)[:, [0, 1, 2, 3]]` be better?

@Yihanhu Do you know that is the reflectance used when training on KITTI? I don't try it on KITTI yet. And could you tell me how much performance is gained...

@Yihanhu The original code stacks all the point cloud frames(~11 frames) into a single frame. I only sample 3 frames from the 11 frames uniformly, and use the reflection channel...

In addition, I didn't use the `encoding.parallel.DataParallelCriterion` successfully, for this issue `'function' object has no attribute 'children'`

Both `DataParallelCriterion` and PyTorch build-in `DataParall` require a torch.module, however, the losses computation in my case is a function instead of a torch.module. So I just use the `torch.nn.parallel._functions.Gather` in...

Hi, thanks for your attention. I'm now adding experiments on the newly released Waymo dataset and the full code will be released in June.

@songheony, my apologies for the late reply. Here is the code for generating our filtered detections ([https://github.com/otakudj/ADSS/blob/master/code/metric_v2.m#L91-L152](url)). This just provides an alternative in comparison with simple NMS or confidence-based filtering...