May I ask how do you calculate the Flow Validity Mask that you described in Section 3.3?
Is this part of code in src/model/tsm/temperal_shift.py?
But there is no cycle consistency here.
And how do you calculate the left_flowmask and right_flowmask?
Another question is:
In line 109, torch.clamp(right_flowmask + (torch.sum(left_feature, dim=2, keepdim=True)==0).float(), 0, 1).int().float().
Why left_feature is used here?
Dear Xueyan,
May I ask how do you calculate the Flow Validity Mask that you described in Section 3.3? Is this part of code in src/model/tsm/temperal_shift.py?
But there is no cycle consistency here.
And how do you calculate the left_flowmask and right_flowmask?
Another question is: In line 109, torch.clamp(right_flowmask + (torch.sum(left_feature, dim=2, keepdim=True)==0).float(), 0, 1).int().float(). Why left_feature is used here?
Many thanks for your help in advance!