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deq-flow's Issues

Questions about loss

Thanks for the great work.

The "fixed-point correction" appears to be applied in a dense manner, as seen in RAFT and similar methods. However, the paper mentions that it is applied in a sparse manner. What are the differences in the results between these two approaches?

Furthermore, it seems that intermediate hidden states need to be stored to compute the fixed-point correction. However, changing the f_thres did not result in any difference in memory usage. Can you explain why this is the case?

How to apply this to my own images?

I want to use the pretrained model in my own images to predict optical flow, how can I do that?
I am new to optical flow. Thanks for your help.

Result conversion ๏ผ

Thanks for sharing this interesting work!

I have a question is that the results obtained by the model be converted into depth?

Parameters of DEQ-RAFT

Hello, I am very interested in your work .I have read your paper"Deep Equilibrium Optical Flow Estimation",I want to know how many parameters the model DEQ-RAFT in Table 1 has.

Run a video

Thank you for this interesting work.

Is there a demo that shows how I could run this over a video and get the optical flow per pair of frames?

checkpoints receipe

can you please explain checkpoints training receipe to me?

as i read and understood,

deq-flow-H-chairs.pth === trained on flyingchairs
deq-flow-H-things-test-1x.pth == trained on 1FlyingChairs+1FlyingChairs
deq-flow-H-things-test-3x.pth == trained on 1FlyingChairs+3FlyingChairs
deq-flow-T-things-test.pth == no idea about this
deq-flow-B-chairs.pth == no idea
deq-flow-B-things-test.pth == no idea
deq-flow-H--chairs.pth == no idea
deq-flow-H-kitti.pth == no idea
deq-flow-H-sintel.pth == no idea
deq-flow-H-things-test-1.pth == no idea
deq-flow-H-things-test-2.pth == no idea
deq-flow-H-things-test-3.pth == no idea

and what is --eval_factor doing?
i didn't fina anything about eval_factor in repo

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