Comments (3)
感谢您关注我们的工作。
网络是以t-1,t,t+1三个时刻的图像作为输入,超分辨t时刻的图像,因此舍弃了第一帧和最后一帧。如果需要对第一帧和最后一帧进行超分辨,可以通过输入1,1,2时刻的图像对1时刻进行超分辨。
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非常感谢!
本人就住在国防科大对面,希望能有机会参观贵实验室。
再次感谢!
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非常欢迎 : )
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Related Issues (18)
- run on CPU only without GPU HOT 2
- Output has different number of frames HOT 1
- low retrained result
- where are pretrained models HOT 1
- About evaluation metric:T-MOVIE,MOVIE and VQM-VFD HOT 2
- Code bug in TestsetLoader? HOT 1
- The result of 31 frames of test video is only 29 frames, and the frames at the beginning and end of the video can't be processed?
- vid4 result with worse quality generated by 'demo_vid4.py' HOT 1
- Results in MSU Video Super Resolution Benchmark
- Where does 31 come from in optical_flow_warp? HOT 1
- 系统找不到指定的路径 HOT 2
- Your Results in New Super-Resolution Benchmarks
- Is it possible to add chop_forward HOT 2
- Will you release code for training ? HOT 2
- About the draft cube (input to SRnet) HOT 2
- Issues with Memory Usage HOT 1
- Availability of training data? HOT 1
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