[HN Gopher] Depth Anything: Unleashing the Power of Large-Scale ...
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       Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
        
       Author : qwertygnu
       Score  : 45 points
       Date   : 2024-01-22 17:08 UTC (5 hours ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | leobg wrote:
       | Impressive demo.
       | 
       | Any FSD startup that put their money on LiDAR is even more
       | screwed now.
        
         | buildbot wrote:
         | Disagree there. Humans have massive compute, dual optics, and
         | amazing filters.
         | 
         | Computer vision has 1-2 of those three, and I don't think we
         | are near an AGI for self driving yet. Driving is IMO, an AGI
         | level task.
         | 
         | Does you dataset have a crocodile in it? Does you monocular
         | depth model get fooled by a billboard that's just a photo?
        
         | pedalpete wrote:
         | That's only a "happy path" attitude.
         | 
         | How well would a moncular path with headlights moving toward it
         | at night operate? How about in rain, snow, or fog?
         | 
         | I'm not saying LiDAR is the only way, but I don't see a reason
         | to use this as a solution.
         | 
         | I'm not saying this isn't valuable. I used to work in
         | 3D/metaverse space, and having depth from a single photo, and
         | being able to recreate a 3D scene from that is very valuable,
         | and is the future.
        
       | buildbot wrote:
       | Very interesting work! More details here: https://depth-
       | anything.github.io/
       | 
       | It seems better overall and per parameter than current work, with
       | relative and absolute measurement.
       | 
       | Is there any research people are aware of that provides sub-mm
       | level models? For 3D modeling purposes? Or is "classic"
       | photogrammetry still the best option there?
        
       | xnx wrote:
       | Very cool to see TikTok sharing its research.
        
       | ClassyJacket wrote:
       | Can someone explain the meaning of labelled vs unlabelled in this
       | context? What kind of information would the labels carry?
       | 
       | Did they have depth maps for all 62 million images or not?
        
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       (page generated 2024-01-22 23:00 UTC)