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Would be great if you could share your 3-5 most exciting developments that weren't discussed mich here.

dagmx 4y ago
My mind might have quite a bit of recency bias since I just wrapped siggraph a few weeks ago (without catching Covid!) so I’m a little scattershot. I might come back to this later to post more concrete lists but here’s what came to mind first. I should add that my point is more that there’s not been a slow down in ML research, and the ebb and flow of interest on HN isn’t indicative of accelerated progress in the field. Simply of what things have captured the public mind. Anyway on to the links… Disney had a slew of papers out this year, the facial motion retargeting ones in particular are very interesting for use in production of films and “metaverse” characters https://studios.disneyresearch.com/machine-learning/ https://studios.disneyresearch.com/machine-learning/ Luma have had a lot of progress in their Nerf capture and on device representation which will likely have huge effects for e-commerce use cases among other things https://captures.lumalabs.ai/unbounded https://captures.lumalabs.ai/unbounded Nvidia released an ML based version of OpenVDB that will potentially improve effects in films, but could be huge for games https://youtu.be/uAs8X5es1DE https://youtu.be/uAs8X5es1DE There were also a ton of neural rendering papers at siggraph that I still need to separate in my head mentally since I saw them presented back to back, so I apologize for just sharing a dump https://twitter.com/neural_fields/status/1555947856271446018?s=21&t=me8E3zuIOR3mLcLLUvFLCw https://twitter.com/neural_fields/status/1555947856271446018... Apple released some neural rendering content too that has a lot of implications for spatial product training https://arxiv.org/abs/2207.13751 https://arxiv.org/abs/2207.13751
- nsxwolf 4y ago
  You started with downvotes but showed up with the links. Neural VDB looks wild - I can see games going nuts with detailed, interactive volumetrics now, with such a tiny memory footprint.

My mind might have quite a bit of recency bias since I just wrapped siggraph a few weeks ago (without catching Covid!) so I’m a little scattershot. I might come back to this later to post more concrete lists but here’s what came to mind first. I should add that my point is more that there’s not been a slow down in ML research, and the ebb and flow of interest on HN isn’t indicative of accelerated progress in the field. Simply of what things have captured the public mind. Anyway on to the links… Disney had a slew of papers out this year, the facial motion retargeting ones in particular are very interesting for use in production of films and “metaverse” characters https://studios.disneyresearch.com/machine-learning/ https://studios.disneyresearch.com/machine-learning/ Luma have had a lot of progress in their Nerf capture and on device representation which will likely have huge effects for e-commerce use cases among other things https://captures.lumalabs.ai/unbounded https://captures.lumalabs.ai/unbounded Nvidia released an ML based version of OpenVDB that will potentially improve effects in films, but could be huge for games https://youtu.be/uAs8X5es1DE https://youtu.be/uAs8X5es1DE There were also a ton of neural rendering papers at siggraph that I still need to separate in my head mentally since I saw them presented back to back, so I apologize for just sharing a dump https://twitter.com/neural_fields/status/1555947856271446018?s=21&t=me8E3zuIOR3mLcLLUvFLCw https://twitter.com/neural_fields/status/1555947856271446018... Apple released some neural rendering content too that has a lot of implications for spatial product training https://arxiv.org/abs/2207.13751 https://arxiv.org/abs/2207.13751

nsxwolf 4y ago
You started with downvotes but showed up with the links. Neural VDB looks wild - I can see games going nuts with detailed, interactive volumetrics now, with such a tiny memory footprint.