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James Perlman
@jperldev
EntrepreNeRF
ArtistLos Angeles, CAJoined June 2016

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Day ~36. Last month, I set out to learn the art of NeRF by building a neural renderer in CUDA, using permissively-licensed resources. I'd call it a success so far. This concludes Zero to NeRF. Stay tuned for what's next: NeRF to Infinity!
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I'm just getting started! Next I'll improve training and rendering speeds. This video is 3261 frames, representing exponential training steps from 0 to 8061. Resolution is 1080x1080, total processing time 7h 46m. A bit slow for today's standards but it'll get there!
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Standing on the shoulders of giants doesn't even come close to what it's been like to build this. The wealth of resources and information available is simply remarkable. And it's a significant understatement to say the people researching this stuff are smart, kind, and helpful.
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Something I've learned from doing this - NeRF is really hard! The hardest thing I've ever attempted. I thought there would be a "Holy shit!" moment a la original NeRF, but it's been more of a slow grind, with each run yielding ~1% higher quality than the last run (at best).
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progress! I think I finally solved that gradient. (huge thanks to ). Now it seems the occupancy grid has a problem... after the first update, about 60% of the cells are culled, but then they all come back over the next 4 occupancy grid updates... any ideas anyone?
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Aight I know it's not a competition, but *MY* NeRF algorithm is ONLY FLOATERS today, so if that's your thing hmu. #OopsAllFloaters
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🔥 Floaters, clouds, things... NO MORE! Announcing the next release of Luma NeRF captures: they are clearer, sharper, and even higher res. And they are here. NOW! lumalabs.ai/ios #3d #ai #nerf #capture 🔊
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All of these are original renders from my shitty NeRF algorithm, the only modification is a black background. I'll admit I think some of them look pretty cool, and it's fun to use my allotment of self-deprecation for a silly post. I will figure this out. It is inevitable. :)
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5. Barnacle Dozer. This was left to the elements for many years, before being unearthed by a well-rendered dozer. I have yet to find the asshole (and their shiny fancy dozer) that left it here for me to look at.
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Shitty dozers, an art gallery of failed NeRF renders. As I build my renderer, I continue to meet failure after failure, likely due to the fact that I don't really know shit about fuck. 1. Lavadozer. This one represents my burning desire to literally just have one good render.
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#NeRF researcher SOS - why is this so lumpy??? and why do infinite values keep appearing in my density field? plz send help
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Zero to NeRF Day 20 Update THE NERF IS NIGH. Training & rendering are implemented but not functional. My renderer outputs this image after 50 iters. It appears to have a periodic pattern 16 pixels wide. Interestingly the network output width is also 16... Data alignment?
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YES!
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Used NeRF to make a "Bullet Time" effect for a friend's wedding. We set up 15 iPhones to capture slow-motion video, then used @NVIDIAAIDev Instant-NGP to train a bunch of NeRFs on the frames. ..need to work on improving the quality / resolution a bit more.
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Zero to NeRF update for ya- It's day 13, I've completed data loading, batch generation, occupancy grid implementation, concatenated MLP architecture (via the Instant-NGP paper), and today I spent 9 hours computing the derivative of the loss function with respect to rgb & sigma...
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5/5) I will end with a failure case that happened about 30 mins later when I tried to get it to rewrite pseudocode for a camera ray generator. It didn't quite understand what to do...Going to try refining this technique but this one was faster to code the old-fashioned way. :P
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4/5) This is a really fun and exciting example of human-guided AI coding, and so fun to use. In about 5 minutes I was able to write a performant multi-threaded image loader, which taught me some new techniques as well. The code works great now!
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