monodepth2 VS IJCAI2023-CoNR

Compare monodepth2 vs IJCAI2023-CoNR and see what are their differences.

IJCAI2023-CoNR

IJCAI2023 - Collaborative Neural Rendering using Anime Character Sheets (by megvii-research)
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monodepth2 IJCAI2023-CoNR
6 4
3,977 783
0.5% 0.5%
0.0 5.5
8 months ago 9 months ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 or later 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.

monodepth2

Posts with mentions or reviews of monodepth2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-24.

IJCAI2023-CoNR

Posts with mentions or reviews of IJCAI2023-CoNR. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing monodepth2 and IJCAI2023-CoNR you can also consider the following projects:

DenseDepth - High Quality Monocular Depth Estimation via Transfer Learning

ml-course - Open Machine Learning course

packnet-sfm - TRI-ML Monocular Depth Estimation Repository

glasses - High-quality Neural Networks for Computer Vision 😎

cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

open_clip - An open source implementation of CLIP.

torchdyn - A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

ZoeDepth - Metric depth estimation from a single image

diffusers-interpret - Diffusers-Interpret 🤗🧨🕵️‍♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.

DeepLearningExamples - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.