@JingZhang617 Hi! Thanks for your excellent works!
In the paper, you mentioned that you used hide-and-seek to generate five ground truths. In the code, the network learns from only one initial ground truth. Could you please give me a favor?
Besides, I generate results for test images using the provided models. I find the results for one image are the same. Could you tell me how to generate diverse outputs like Figure 8?
@JingZhang617 Hi! Thanks for your excellent works! In the paper, you mentioned that you used hide-and-seek to generate five ground truths. In the code, the network learns from only one initial ground truth. Could you please give me a favor?
Besides, I generate results for test images using the provided models. I find the results for one image are the same. Could you tell me how to generate diverse outputs like Figure 8?
Looking forward to your answer. Thanks again!