Comments (2)
From what I have observed I think the author was trying to train the first network to generate good optical flows. The second network adds small adjustments to this flow along with visibility maps. The visibility maps enforce the second network to ignore areas with less confidence from the warped images (g_I0_F_t_0_f and g_I0_F_t_0_f). This also causes the flow in those areas to be ignored as they are inconsequential to the final result (as those pixels are masked). This is just how I understand it and the actual reason might be something like this works better.
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Thanks for your reply and I think your understanding is reasonable.
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Related Issues (20)
- ffmpeg error while running evaluation code. HOT 1
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- Error converting file:D:\Coding\JAVASCRIPT\recless\out\4fpsRecording.mkv. Exiting.
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- Training
- Objective metrics
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