I MOVED I MOVED I MOVED I MOVED I MOVED
follow me at https://leporyd.tumblr.com please
My blog is basically fucked server side so I moved because it started to piss me off because I couldn’t RB on mobile ect
R blog pls
@leporyd2 / leporyd2.tumblr.com
follow me at https://leporyd.tumblr.com please
My blog is basically fucked server side so I moved because it started to piss me off because I couldn’t RB on mobile ect
R blog pls
follow me at https://leporyd.tumblr.com please
My blog is basically fucked server side so I moved because it started to piss me off because I couldn't RB on mobile ect
im gonna be moving blogs soonish maybe, mostly because this one is broken and sideblogs literally wont delete. username will be the same as this
im…. real? im…. gotdamn…. alive?
Machine Learning research from University of Nottingham School of Computer Science can generate a 3D model of a human face from an image using neural networks:
3D face reconstruction is a fundamental Computer Vision problem of extraordinary difficulty. Current systems often assume the availability of multiple facial images (sometimes from the same subject) as input, and must address a number of methodological challenges such as establishing dense correspondences across large facial poses, expressions, and non-uniform illumination. In general these methods require complex and inefficient pipelines for model building and fitting. In this work, we propose to address many of these limitations by training a Convolutional Neural Network (CNN) on an appropriate dataset consisting of 2D images and 3D facial models or scans. Our CNN works with just a single 2D facial image, does not require accurate alignment nor establishes dense correspondence between images, works for arbitrary facial poses and expressions, and can be used to reconstruct the whole 3D facial geometry (including the non-visible parts of the face) bypassing the construction (during training) and fitting (during testing) of a 3D Morphable Model. We achieve this via a simple CNN architecture that performs direct regression of a volumetric representation of the 3D facial geometry from a single 2D image. We also demonstrate how the related task of facial landmark localization can be incorporated into the proposed framework and help improve reconstruction quality, especially for the cases of large poses and facial expressions.
There is an online demo which will let you upload an image to convert and even save as a 3D model here
its honestly the most harrowing experience to see someone on tumblr vociferate a really dumb opinion that you held as a teenager so you go “ah we all make mistakes i remember being 15″ and it turns out theyre almost 30
jeff kaplans apparently long and lurid history of writing expletive laced and vaguely overreactive rants about the everquest developers and his current career of talking about overwatch updates as if he is perpetually on the brink of very polite tears reminds of that episode of the simpsons where they reveal that flanders used to be the most destructively angry child alive and could still, in fact, snap at any moment
me, a furry barging in uninvited into my friend’s conversations
if you call women “females” i automatically do not trust or like you
you really wont like the military then buddy
jokes on you, i already hate the military
Ghost stories is a ride and I highly suggest watching the English dub
put the donuts down bigigitititititittigigtigititigigitititigititivgitigggigitity
Hey remember early last year when the Large Hadron Collider overloaded and broke down and people were like “phew good thing nothing weird happened like a shift in reality.” Maybe it’s time to revisit that.