GwcNet
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Group-wise Correlation Stereo Network, CVPR 2019
 尊敬的郭老师,我在跑kitti15进行训练时,出现如图所示的报错,不太懂该怎么修改,希望您百忙之中抽空看一下,pytorch用的是1.8版本的
Hi,thank you very much for your great work! The image size to test SceneFlow datasets in your paper is 960x540,  But in your code (sceneflow_dataset.py line 61), it's 960x512...
I am a freshman. I use Pytorch1.8.0 but got this error, but do not know how to fix... `Traceback (most recent call last): File "main.py", line 201, in train() File...
作者您好,原谅我使用汉语请教您,(我英文水平太菜了)。 1、对于SceneFlow数据集的评估,普遍都使用EPE(也就是MAE)作为评估标准,而且代码里也可以实现评估函数进行评估。 2、对于KITTI2012数据集,评价标准有Noc和Occ(All)的>2px, >3px, >4px, >5px以及Mean Error的错误率和错误像素数的评估,这些评估都是需要在自己代码里面实现它们的函数吗?还是需要提交到KITTI官网上生成评测结果呢? 3、对于KITTI2015数据集,评价标准里有All(Occ)和Noc的D1-bg,D1-fg,D1-all的错误率评估,需要自己在代码里面实现评估函数吗,还是必须提交到KITTI官网上评测结果呢? 4、对于kitti12来说,所以的评估标准可以自己代码实现;但是对于kitti2015来说,自己无法实现评价代码,D1-bg,D1-fg,D1-all这些怎么实现? 5、而且发论文的话,KITTI12和15的实验数据必须来自kitti的官方网站吗? 对于以上问题,目前还是比较迷惑的,kitti网站好像说是不能用于调试程序,每个人只能在规定时间内提交一次把,也不能申请多个账号吧。 所以对于这些评价标准的问题,还望作者大佬您能在百忙中抽出时间不吝赐教,万分感谢!!!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~小白先行谢过!!!!!!!
The training time does not decrease by increasing the batch size. When I move the last two hourglass modules and set batch size = 4, it takes about 3 hours...
hi, we use proposed model loss to optimize, however it stops converging at about 0.21 in the second epoch, is it a bug or it converges quite slowly at this...
Hello, when I infer the sceneflow dataset using your pretrained model, the result seems different from your paper result. **The EPE I get is 0.823**, and your paper result is...
I would like to ask the author, if the size of the image used for network training is 960x540, then when I want to use this network test, the resolution...
感谢您公开代码,请问您是怎么保存sceneflow数据集生成的视差图