Jack Rao
Jack Rao
Hello, I have run this code too. if It uses CPU, it can work. However, if I use GPU, it can't work. I install the cuda 10.1. And I found...
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@ranahanocka, Thanks for you. I have run it successfully on GPUs. I found that the problem caused by CUDA on the system. My CUDA on the system is 9.2. However,...
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> > Hi, I'm using this command line: > > `CUDA_VISIBLE_DEVICES=0,1,2,3 python3 train_autodeeplab.py --dataset coco --filter_multiplier 4 --resize 358 --crop_size 224 --batch-size 24` > > I'm trying to understand why...
亲爱的作者同志, GA-Net,我个人一直认为是一个非常非常棒的工作,也是我一直崇拜、赞扬和推荐的文章。 这篇DSM的文章,我相信也是非常棒的工作。但是,我认为其中的表格3是不严谨的(ETH3D部分)。 我们直接用了GA-Net中,给的10代模型测试了ETH3D中的训练集。我们发现得到的结果比DSM论文中要很好多(网站上只有2像素和4像素的结果,我们可以断定3像素的结果应该介于2像素和4像素之间)。    此外,我们也用GWC-Net给的sceneflow预训练模型去测试了相关数据,发现KITTI和ETH3D中结果应该比DSM论文中给出的结果要好很多。    我们组与GWC-Net没有任何的利益关系。只是单纯地好奇为什么得到的结果有如此大的不同? Dear author, GA net, which I have always considered to be a very, very excellent job, is also...
> @RaoHaocheng I don't know how you retrain the gwcnet. But Eth3D dataset is in gray style. All the models are trained with RGB color images. The evaluations test the...
Hello,I'm not an author in DSM-Net, but we find a project about SGM based on openCV (python or cuda version) that can work better than results in DSM-Net. you can...
I see a lot of people say that the gcNet can't achieve the performance as the paper show. I write gcnet based on tensorflows, can't get the same performance too....
I met the same problem