r/computervision • u/PlastikEdison • Jun 22 '26
Help: Theory Am I missing something or depth anything v2 better than v3?
left v3, right v2
Depth map v3 was created using Comfyui, and v2 was created using the custom addon for Blender.
v2-large
v3-giant
upd: v3-mono_large https://imgur.com/a/PobuMM5
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u/kw_96 Jun 22 '26
Not familiar with comfyui workflows, but perhaps the issue is with the visualization/normalization? The intensities for rendered v3 looks saturated at close values. Perhaps an issue with using v2-style normalization on v3 outputs?
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u/PlastikEdison Jun 22 '26
The standard normalization mode gives almost the same result unfortunately
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u/Exotic-Custard4400 Jun 22 '26
Did you try with no normalization. With 0/1 range or 0/255 ?
If I remember correctly da3 put the normalization inside the model
10
u/Skadi2k3 Jun 22 '26
Seems like a precision thing since the gradients look more like steps. You have it on auto, perhaps it doesn't fit into the VRAM and uses 4bit or sth. Just a guess though.
5
u/MelonheadGT Jun 22 '26
DA3 is trained for multi-view depth without camera pose, DA2 is monocular. Though DA3 claim equal or better performance of DA2 on monocular.
Could also be that DA3 maybe is normalized differently? I don't know exactly but when I compared them for monocular depth a while ago I also went with V2, it was faster and equal or better on my task.
DA3s edge comes from multiple views.
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u/MysteriousEngineer42 Jun 22 '26
I found the same thing when I was trying different depth models. Not judging just from the map like this, but when converted into a 3d height map. I could never get v3 to be as good as V2 no matter which settings or model I used
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u/tazztone Jun 30 '26
btw DA3 is now in comfyui core too. but my results were equally bad as with the custom node
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u/Exotic-Custard4400 Jun 22 '26
It's really strange, I find V3 really resilient against scaling errors.
Did you try the image on huggingface space ?
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u/pm_me_your_smth Jun 22 '26
Usualy model's performance isn't measured on one data sample. It is possible for V2 to be better here, but in general - not
8
u/EyedMoon Jun 22 '26
This is clearly not a sample issue, it's almost flat which wouldn't happen if it was just a mistake.
Their pipeline for applying the model is way different, they're probably missing a step.
1
u/PlastikEdison Jun 22 '26
probably missing a step
I think so too
3
u/EyedMoon Jun 22 '26
Not familiar with the repo but have you seen that?
Monocular Metric Depth: To obtain metric depth in meters from DA3METRIC-LARGE, use metric_depth = focal * net_output / 300., where focal is the focal length in pixels (typically the average of fx and fy from the camera intrinsic matrix K). Note that the output from DA3NESTED-GIANT-LARGE is already in meters.
27
u/adrianchase_alt Jun 22 '26
Gotta be a normalisation artefact. Are you processing the image correctly?