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feinanshan avatar feinanshan commented on August 22, 2024

Hi, the t1 and t2 here are Temporal Relevance coefficients.

def forwarp_mframe_mask(tenIn1, tenFlow1, t1, tenIn2, tenFlow2, t2, tenMetric1=None, tenMetric2=None):

Please refer to the following section of the paper.

image

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Amazingren avatar Amazingren commented on August 22, 2024

Hi @feinanshan

Oh, my bad~ thanks a lot for the quick and kind explanation :)

By the way, If it is possible and when you are free, let's have a quick discussion here about the splatting task via M2M:

For splatting, let's use I_0 and forward optical flow flow_forward to warp I_0 to I_1.

Hence, the fltTime t0 and t1 should be set to t0=1 and t1=1-t0=0, right?

Based on this, now the temporal relevance coefficientst1_temporal = t1 = 0 and t2_temporal = t0 = 1,

so for the flowing line:

tenIn = torch.cat([tenIn * td*(tenMetric).clip(-20.0, 20.0).exp(), td*(tenMetric).clip(-20.0, 20.0).exp()], 1)

The inputs for softsplat_func.apply(tenIn, tenFlow) now are:

  • tenIn: torch.cat([tenIn * 0 * (tenMetric).clip(-20.0, 20.0).exp(), 0 * (tenMetric).clip(-20, 20).exp()], 1)
  • tenFlow:flow_forward

Now the tenIn is the point that I am not totally clear about. So if I want to do splatting with M2M, is there any suggestion on how to solve this problem?

Bests,

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feinanshan avatar feinanshan commented on August 22, 2024

Hi, yes in this extreme case of t0=1, tenIn (from I_0 to t0) will be zero which means no information will be warped from I_0.
Yet note that we are interpolating with two frames, hence at the same time, the tenIn (from I_1 to t0) will be equivalent to I_1 itself.

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Amazingren avatar Amazingren commented on August 22, 2024

Hi, yes in this extreme case of t0=1, tenIn (from I_0 to t0) will be zero which means no information will be warped from I_0. Yet note that we are interpolating with two frames, hence at the same time, the tenIn (from I_1 to t0) will be equivalent to I_1 itself.

Got it!
thanks a lot! :)

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