Always wanted to create some fast paced game! Finally got to start it!
I will definitely evolve it over time.
All done in my spare time with help of agentic coding!
89 karma · joined November 2, 2023
Email: mshailesh2018@gmail.com
Always wanted to create some fast paced game! Finally got to start it!
I will definitely evolve it over time.
All done in my spare time with help of agentic coding!
This is one of the most overlooked problems in generative AI. It seems so trivial, but in fact, it is quite difficult. The difficulty arises because of the non-linearity that is expected in any natural motion.
In fact, the author has highlighted all the possible difficulties of this problem in a much better manner.
I started with some simple implementation by trying to move segments around the image using some segmentation mask + ROI. That strategy didn't work out, probably because of some mathematical bug or data insufficiency data. I suspect the later.
The whole idea was to draw a segmentation mask on the target image, then draw lines that represent motion and give options to insert keyframes for the lines.
Imagine you are drawing a curve from A to A. You divide the curve into A, A_1, A_2... B.
Now, given the input of segmentation mask, motion curve, and whole image, we train some model to only move the ROI according to the motion curve and keyframe.
The problem with this approach is in sampling the keyframe and matching consistencies --making sure RoI represents same object-- across subsequent keyframes.
If we are able to solve some form of consistency, this method might be able to give enough constraints to generate viable results.
Remote: Yes
Willing to relocate: Yes
Technologies: Python, C++, CUDA, Blender, Unity3D
Resume: https://shailesh-mishra.com/resume.pdf
Email: check bio in HN or in resume
More info:
I am a recent graduate specialized in computer graphics (character animation) and computer vision (inverse rendering). I am currently in Germany. I would be happy to move as long as I get a proper visa sponsorship.
I am comfortable with anycode base of any kind. My personal website highlights the kind of projects I did in the past and my university.
Regarding LLMs, I am one of the co-authors on indirect prompt injection paper [1]. I also happen to have intuition of the maths behind diffusion. Meaning, I am also open to any GenAI related roles.
Feel me to contact me for an open position.
NGL, because this is actually my dream job.
"We first learn a vocabulary of latent quantized embeddings, using graph convolutions, which inform these embeddings of the local mesh geometry and topology. These embeddings are sequenced and decoded into triangles by a decoder, ensuring that they can effectively reconstruct the mesh."
This idea is simply beautiful and so obvious in hindsight.
"To define the tokens to generate, we consider a practical approach to represent a mesh M for autoregressive generation: a sequence of triangles."
More from paper. Just so cool!
Also, can someone benchmark it on m3 devices? It would be cool to see if it is worth getting on to run these diffusion inferences and development. If m3 pro can allow finetuning it would be amazing to use it on downstream tasks!
Seriously nothing compares to the typing experience of split keyboard. Open shoulders are great, relaxed arms and wrists is a blessing, then there are layers. Those are sooooo awesome when used in correct way!
It has really been amazing experience. I can't imagine going to normal keyboards.
And the shoulders, the best part of split keyboard is the open shoulders! It feels good to work on the split keyboard. One of the best investment!
I am glad you created a layout for yourself!
Considering speed, I am all recovered and even surpassed by QWERTY speed. I am average (~60wpm) when it comes to typing speed so it wasn't hard to catch up to it.
My switching experience was also similar to yours. Get to ~35 wpm and start using. It took me 14 hrs to reach there (1hr deliberate practice everyday for 2 weeks.)