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gangweiX / Fast-ACVNet

[TPAMI 2024] Fast-ACV: Fast Attention Concatenation Volume for Accurate and Real-time Stereo Matching

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Fast_ACVNet and Fast_ACVNet_plus

Torment123 opened this issue · comments

commented

Hi, I noticed that there's a fast_acvnet_plus in the model folder, which is implemented differently compare to the paper (the correlation is computed between feature maps of 1/4 of the original resolution instead of 1/8), So if I want to reproduce the result of fast_acvnet, I think I should instead use the model in Fast_ACV.py ? Also, what benefit of fast_acvnet_plus compare to the vanilla fast_acvnet? Thanks in davance

commented

Thank you for your attention. The fast_acvnet_plus constructs a higher resolution correlation (i.e. 1/4), which can obtain more accurate attention weights.

commented

I see, thanks for your fast reponse