[HN Gopher] Degas: Detailed Expressions on Full-Body Gaussian Av...
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       Degas: Detailed Expressions on Full-Body Gaussian Avatars
        
       Author : smusamashah
       Score  : 136 points
       Date   : 2024-08-21 13:52 UTC (5 days ago)
        
 (HTM) web link (initialneil.github.io)
 (TXT) w3m dump (initialneil.github.io)
        
       | instagraham wrote:
       | > see project > excited to try it > code (coming soon) > bookmark
       | project > forget about project
       | 
       | Barring the obvious deepfake implications though, I'd be excited
       | to see a new era of SFM-style content made with this
        
         | apeescape wrote:
         | Video games with characters looking this good would be amazing.
        
           | littlestymaar wrote:
           | For animations video games use motion capture already, and an
           | interesting thing is that you cannot ask your mocap actor to
           | act normally and expect the result to look good, for some
           | reason natural motion is not desired in games and studios
           | both ask the actor to play in a very specific way, and then
           | animation artists still have lots of work tweaking the
           | animations so that it looks good.
           | 
           | It's the same reason why acting on a theater scene doesn't
           | just requires that you project yourself in the role and try
           | embody the character but also adapt your motion and
           | expressions so they can be understood by the public sitting
           | afar.
        
             | pedalpete wrote:
             | That's super interesting. Do you think that a model could
             | be trained to exaggerate the motions necessary, and then
             | that output could be splatted? There is probably enough
             | mocap data already to "rebuild" games with new characters
             | using similar techniques.
             | 
             | Or am I way off here?
        
       | olivierduval wrote:
       | It's so amazing that it's frightening !!!!
       | 
       | With that kind of technology, what are the key problem still to
       | be solved before being massively applied to deepfakes ? More
       | specifically:
       | 
       | - how much datas (pictures or video) of the "target" is needed to
       | use this ? Does it requires a specific lighting, a lot of
       | different poses... or is it possible to just use some "online"
       | videos (found on tiktok for example) or to record the "target" in
       | the street with a phone ? How is it to create a "virtual
       | doppelganger" ?
       | 
       | - when there is a "target" model, is it possible to use this in
       | realtime ? How much power would it need ? A small laptop ? A big
       | machine in the cloud ? Only a state-sponsored infrastructure ?
       | 
       | It looks like this technology has a real potential to
       | "impersonate" anybody really efficiently
        
         | bilbo0s wrote:
         | It's not clear to me that you can have an unrelated target?
         | 
         | But that's a good question, can you take a canonical pose of
         | peter, and make it perform an animation of jenni's dance? Jenni
         | will have breasts and hips. Those offsets in the texture map
         | could be enough to throw it, who knows?
         | 
         | At least for the work they did, it seems they did all the work
         | for each subject separately. Which is useful, but it's
         | obviously going to constrict the use cases for the technology.
         | 
         | I could be misunderstanding however. I only looked at it for
         | the past 5 or 6 minutes.
        
         | kortex wrote:
         | I worked on a DARPA anti-deepfakes project up until spring
         | 2021, so just before the real tidal wave of generative AI. At
         | that time, state of the art (of publicly known tech) required a
         | few hours of target footage to train something passably
         | deepfaked. Since then, there's been huge advancements in the
         | generalizability of models. I don't know how little the
         | threshold is, but it has gone from "only really feasible on
         | celebs/politicians/folks with extensive video presence" to
         | "feasible from a handful of videos". Like your average
         | American's social media footprint.
         | 
         | You still need a pretty beefy rig (array of multiple 4090 gpus)
         | to do convincing video generation in a non-glacial amount of
         | time but it's totally possible with readily available hardware.
         | 
         | The bigger problem is actually "cheapfakes", so many people are
         | so confirmation-biased that they will readily amplify even
         | poorly put-together disinformation.
        
           | aaroninsf wrote:
           | Cheapfakes... TIL.
           | 
           | Instantly useful thank you!
        
       | jimmySixDOF wrote:
       | So much cool work bringing realism to Gaussian sources I think
       | avatar mediated collaboration will get across the uncanny valley
       | so where you are and how well you can communicate are not related
       | anymore.
       | 
       | Also if you like Degas, this is another state of the art project
       | in progress called VR-GS: A Physical Dynamics-Aware Interactive
       | Gaussian Splatting System in Virtual Reality
       | 
       | https://yingjiang96.github.io/VR-GS/
        
       | SiempreViernes wrote:
       | The second to last video shows a Gaussian splatting advantage I
       | didn't think of: when gaussians clip into each other the failure
       | is more gradual than when polygons do it.
        
       | jgord wrote:
       | scary good demos.
        
       | MPSimmons wrote:
       | Still some weaknesses with cloth but that's really impressive
        
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