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I have the same confusion. And I have tried to use result_depth = (1 - sparse_mask) * result_depth + sparse_mask * sparse_depth
which is as your description in your paper (or it's a mistake?), but in this case, the model can learn nothing.
And it seems that the sparse_depth is only used to compute this sparse_mask, and the model will complete the depth map based on the estimated coarse depth (raw_depth_input in your codes). Why does it work well for depth completion? @XinJCheng
@UltronAI@mqchen1993 I think it's pointed out in the paper sec 3.3.1 clearly with the exact update equation and explanation ?
The sparse_depth is embedded to a hidden space(blur_depth [at sparse_mask position] ).
raw_depth_input = blur_depth
...
if sparse_depth is not None:
result_depth = (1 - sparse_mask) * result_depth + sparse_mask * raw_depth_input
你好,我有一个疑惑。为了保留sparse depth上的有效值,为什么不是用sparse上的值替换,而是用blur_depth。blur_depth是网络预测的,这个不一定准确啊?请麻烦帮我解答一下,谢谢!
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