[HN Gopher] Point-E: Point cloud diffusion for 3D model synthesis ___________________________________________________________________ Point-E: Point cloud diffusion for 3D model synthesis Author : smusamashah Score : 120 points Date : 2022-12-20 11:15 UTC (11 hours ago) (HTM) web link (github.com) (TXT) w3m dump (github.com) | acreatureofhab wrote: | This is bananas... the metaverse may be possible with tech like | this being available for the masses. | bilsbie wrote: | Can I 3d print this? | tarr11 wrote: | See also Magic3D from Nvidia, which generates mesh models. | | https://deepimagination.cc/Magic3D/ | dr_dshiv wrote: | Anyone else using Kaedim to translate 2d images to 3d models? | https://www.kaedim3d.com/ | | We made some midjourney lamps--and then printed them! Pretty | cool. | virtualritz wrote: | Looking at their prices and the (impressive) quality of the | mesh topology in the demo movie they have on their web page | (the rat) I couldn't help but think this a front that pretends | to use pure AI but actually has real people (specialized | mechanical turks) involved. | | Specifically for guiding generation of the mesh from a possibly | AI-generated point cloud (PTC). E.g. using manual contraints on | an mostly automatic quad (re-)mesher ran as a post process on | the triangle soup obtained from meshing the original, AI- | generated PTC. | | I.e.: | | 1. AI-generate PTC from image(s). | | 2. Auto-generate triangle mesh via marching cubes or whatever | from PTC. | | 3. Quad re-mesh with mesh-guided automatic constraint discovery | (think edges, corners etc.). | | 4. Manual edit quad-mesher constraints. | | 5. Quad re-mesh. | | That would explain their pricing which seems a tad too high for | a fully automatic solution. $600 for 30 models x 10 iterations. | I.e. each iteration would cost $2. | | Or maybe it's just so niche this is simply because of number of | users for now and indeed fully automatic. | | Curious to hear what other people involved in 3D and cloud | compute think. | punkspider wrote: | How long does it take to convert 2d to 3d? | | I found out about Kaedim a few weeks ago and when I saw this | repo, it came to my mind as well. | dang wrote: | Related: | | https://arxiv.org/abs/2212.08751 (via | https://news.ycombinator.com/item?id=34060986) | | https://techcrunch.com/2022/12/20/openai-releases-point-e-an... | (via https://news.ycombinator.com/item?id=34069231) | | https://twitter.com/drjimfan/status/1605175485897625602 (via | https://news.ycombinator.com/item?id=34068271) | | (but no meaningful comments at those other threads) | pavlov wrote: | Maybe the lack of commenter enthusiasm is because point clouds | are fairly specialized. Most people don't have interesting | point cloud data lying around to test this with, or the means | to capture such data. | | 3D sensors are slowly but surely becoming more common. The | iPhone Pro series has one, and AR hardware designs tend to | include these capabilities. So this model synthesis seems a bit | ahead of the curve, in a good way. | JayStavis wrote: | Agree with you that point clouds aren't mainstream at all and | most people aren't sure what they'd use them for. | | I think the premise of this is text-to-3D, and that because | it's quicker generations you don't really need anything | besides a GPU to start playing around with it. | uplifter wrote: | anyone with a recent (last five years) iphone or ipad has the | means to generate point cloud data using the depth sensors. | speedgoose wrote: | Do you have an app to recommend? And does it work well on | small objects? The apps I tried were not very impressive. | uplifter wrote: | Sorry I don't know any store apps for such, my only | experience is through personal corespondance/demos | with/by developers experimenting with the hardware | feature and sdk. Quick googling turns up some contenders | but I can't vouch for them: | | https://apps.apple.com/ca/app/point-cloud-ar/id1435700044 | | https://apps.apple.com/ca/app/point-precise/id1629822901 | 9wzYQbTYsAIc wrote: | > Maybe the lack of commenter enthusiasm is because point | clouds are fairly specialized. | | Please correct me if I am wrong. | | The pointcloudtomesh notebook seems to be be able to output | something could be converted for 3d printing purposes. | | I haven't yet attempted to do so, but that does seem like an | exciting and general purpose use case. | FloatArtifact wrote: | An alternate approach, although brewed force would be generating | an image set using prompts and then using photogrammetry to | convert to 3D. Either way, I'm excited for this space to grow | both in 3D prompt generation and alternate inputs through | scanning. There's a difference between creative and functional | use case. | cdcox wrote: | Web demo for anyone interested takes about 2 minutes to run: | https://huggingface.co/spaces/osanseviero/point-e | | Seems super fast, some are saying 600x faster [0], than than the | version made off of Google's paper. But it is a little less | accurate. Point clouds are less useful but some on Reddit and the | authors have tools to try to convert to meshes [1][2]. It does | feel like stable diffusion level generation of good 3d assets is | right around the corner. It will be interesting to see which tech | wins out, whether it's some variant of depth estimation like sd2 | and non ai tools can do, object spinning/multi angle view like | Google's tool does, or whatever this tool does. | | [0] | https://twitter.com/DrJimFan/status/1605175485897625602?t=H_... | | [1] | https://www.reddit.com/r/StableDiffusion/comments/zqq1ha/ope... | | [2] | https://github.com/openai/point-e/blob/main/point_e/examples... | numpad0 wrote: | > The main problem with mesh generation from stuff like this is | that usually the topology is a mess and needs a lot of cleanup | to be useuable. It's not quite so bad for static non deforming | objects but anything that needs to be animated deforming or | that is organic looking would likely need retopologizing by | hand. > > That's one of the worst parts of 3D modeling so it's | like you're getting the AI to do the fun part and leaving you | to do all the boring cleanup process. | | From [1]. Seems like there is a pattern of "AI asked to | generate final results with only final results to learn from, | immediately asked for the apple in the picture" in AI | generators. I suppose lack of specialization in application | domains of NNs is a deliberate design choice for these high- | profile projects, in a vague hope of simulating emergent | behaviors as seen in the nature and avoiding to be another | expert system(while being one!), but that attitude seems | limiting usefulness, here and again. | codetrotter wrote: | > Web demo for anyone interested takes about 2 minutes to run: | https://huggingface.co/spaces/osanseviero/point-e | | It's a fun demo. Worth to note that on mobile it didn't include | any button to download the generated point cloud data itself, | at least not that I could find. Might be the same on desktop | also. | | Additionally I think the amount of time taken depends on the | amount of visitors. I had to wait about 7 minutes for it to | finish. | speedgoose wrote: | > We would like to thank everyone behind ChatGPT for creat-ing a | tool that helped provide useful writing feedback. | | I wonder how much of the research paper is written by ChatGPT. ___________________________________________________________________ (page generated 2022-12-20 23:00 UTC)