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Concerns about comparisons #20

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DachunKai opened this issue Oct 25, 2023 · 1 comment
Open

Concerns about comparisons #20

DachunKai opened this issue Oct 25, 2023 · 1 comment

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@DachunKai
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Excellent work!

Would it be appropriate to consider comparing it with two-stage methods that incorporate enhancement algorithms for various common corruption types along with depth estimation? For example, when dealing with foggy conditions, could we explore a comparison with the approach of 'defoggy first, followed by depth estimation'?

@ldkong1205
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Hi @DachunKai, thanks for asking this interesting question!

To ensure fairness in comparison, we did not include augmentation techniques like de-foggy in our benchmarks. However, we agree that using some de-noising approaches is promising in improving the OoD robustness. Several of our participants in the RoboDepth Challenge have already proven the effectiveness of this two-stage method. You can find more details from the competition report (https://arxiv.org/abs/2307.15061).

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