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maximelianos avatar maximelianos commented on June 21, 2024 1

The code is misleading - MaskFlownet model does not return occlusions. If you look at the paper, this model is composed of several MaskFlownet_S, with no occlusion output in the end (figure 2 in the paper).

Thus, occlusions can be obtained only from running MaskFlownet_S, and the results are similar to the visualization.
You don't need to use normalisation there, checking min and max shows that occlusions are in range [0, 1]. Meanwhile when I ran MaskFlownet, the output was obviously optical flow, not occlusions.

from maskflownet.

lzh00 avatar lzh00 commented on June 21, 2024

@lizzardhub Thank you very much. I have tried to use MaskFlownet_S configuration and model, the output occ_mask is the same with paper claimed.

from maskflownet.

Yugt4732 avatar Yugt4732 commented on June 21, 2024

Thanks a lot. But, how can I infer in my own data by MaskFlownet_S?

@lizzardhub Thank you very much. I have tried to use MaskFlownet_S configuration and model, the output occ_mask is the same with paper claimed.

The code is misleading - MaskFlownet model does not return occlusions. If you look at the paper, this model is composed of several MaskFlownet_S, with no occlusion output in the end (figure 2 in the paper).

Thus, occlusions can be obtained only from running MaskFlownet_S, and the results are similar to the visualization.
You don't need to use normalisation there, checking min and max shows that occlusions are in range [0, 1]. Meanwhile when I ran MaskFlownet, the output was obviously optical flow, not occlusions.

from maskflownet.

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