magic3d-pytorch VS Papers-in-100-Lines-of-Code

Compare magic3d-pytorch vs Papers-in-100-Lines-of-Code and see what are their differences.

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magic3d-pytorch Papers-in-100-Lines-of-Code
1 3
339 594
- -
5.2 5.4
over 1 year ago 18 days ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

magic3d-pytorch

Posts with mentions or reviews of magic3d-pytorch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-27.

Papers-in-100-Lines-of-Code

Posts with mentions or reviews of Papers-in-100-Lines-of-Code. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing magic3d-pytorch and Papers-in-100-Lines-of-Code you can also consider the following projects:

point-e - Point cloud diffusion for 3D model synthesis

EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

text2mesh - 3D mesh stylization driven by a text input in PyTorch

taichi-ngp-renderer - An Instants-NGP renderer that has been implemented using Taichi

GET3D

CelebV-HQ - [ECCV 2022] CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

stable-dreamfusion - Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion.

rtdl-num-embeddings - (NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning

audio-diffusion-pytorch - Audio generation using diffusion models, in PyTorch.

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

artbench - Benchmarking Generative Models with Artworks

MTR - The official implementation of the paper "Rethinking Data Augmentation for Tabular Data in Deep Learning"