[HN Gopher] Extreme video compression with prediction using pre-...
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       Extreme video compression with prediction using pre-trainded
       diffusion models
        
       Author : john_g
       Score  : 44 points
       Date   : 2024-02-19 14:51 UTC (8 hours ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | zaptrem wrote:
       | Can you share example videos?
        
         | yonixw wrote:
         | Googling gave me the article:
         | https://www.arxiv.org/abs/2402.08934
         | 
         | Which have examples in it.
        
       | mjevans wrote:
       | I wonder how effective a speed focused variation could be for
       | quality among 264, 265, and AV1.
        
       | IshKebab wrote:
       | > It can be observed that our model outperforms them at low
       | bitrates
       | 
       | It can? Maybe I'm misunderstanding the graphs but it doesn't look
       | like it to me?
        
         | astrange wrote:
         | Graphs (especially PSNR) aren't a good way to judge video
         | compression. It's better to just watch the video.
         | 
         | Many older/commercial video codecs optimized for PSNR, which
         | results in the output being blurry and textureless because
         | that's the best way to minimize rate for the same PSNR.
        
       | Animats wrote:
       | Extreme compression will be when you put in a movie and get a
       | SORA prompt back that regenerates something close enough to the
       | movie.
        
         | squokko wrote:
         | I can imagine that in under 5 years, the movie's script plus
         | one example still photo for each scene could do the job.
        
           | bsenftner wrote:
           | If we get anywhere close to that, coming up with a new
           | economics model is going to be the prompt we'll be giving the
           | AGI when it's ready. We'll need it.
        
       | sbalamurugan wrote:
       | It's uncanny how much of the current stuff has been predicted by
       | the sitcom -"Silicon Valley"
        
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       (page generated 2024-02-19 23:00 UTC)