v8-perf VS pifuhd

Modern v8 does on disk byte code caching, things have come a long way since Palm. In many cases PWAs have faster startup than native apps (also the on disk size of a PWA is usually an order of magnitude smaller than a similar native app.)

https://v8.dev/blog/code-caching-for-devs

https://github.com/thlorenz/v8-perf/blob/master/snapshots%2B...

For low-level code (i.e. anything involving bit twiddling, binary encoding, etc.), you'll want to use the profiler in Node.js (your code editor may have support) or Chrome (see this article). This guide to performance in the V8 engine may help.

V8 has optimized new JavaScript language features (2018): https://github.com/thlorenz/v8-perf/blob/master/language-features.md

PIFuHD (Generate 3d Models from a single image) https://github.com/facebookresearch/pifuhd

git clone https://github.com/facebookresearch/pifuhd

Code for https://arxiv.org/abs/2004.00452 found: https://github.com/facebookresearch/pifuhd

I'm very interested in converting images to 3d models. Really cool tech that feels like it's nearly there.

Have you by chance seen any of the work Facebook has been doing related to the 2d to 3d conversions?

https://github.com/facebookresearch/pifuhd

Yes you're correct. That's why I thought having a dome of raspberry pis around a turntable, getting multiple angles at once, but also the movement would provide a solid dataset to be able to train a neural network to generate a 3D model of a person, or an object or possibly even an animal from a single photo, sort of like PifuHD.

PIFuHD

facebookresearch/pifuhd (Python): High-Resolution 3D Human Digitization from A Single Image.