https://alexswong.github.io/GenAI4Good/

GenAI4Good global open source initiative for accelerating machine learning for promoting responsible creation and deployment of generative AI for good.
https://alexswong.github.io/GenAI4Good/

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GenAI4Good global open source initiative for accelerating machine learning for promoting responsible creation and deployment of generative AI for good.

• Host: GitHub
• URL: https://alexswong.github.io/GenAI4Good/
• Owner: AlexSWong
• License: mit
• Created: 2023-05-08T23:12:39.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-02-12T13:09:32.000Z (11 months ago)
• Last Synced: 2024-02-12T14:53:31.030Z (11 months ago)
• Size: 25.2 MB
• Stars: 5
• Watchers: 1
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


# GenAI4Good Open Initiative

The tremendous recent advances in generative artificial intelligence techniques have led to significant successes and promise in a wide range of different applications ranging from conversational agents and textual content generation to voice and visual synthesis. Amid the rise in generative AI and its increasing widespread adoption, there has been significant growing concern over the use of generative AI for malicious purposes ranging from disinformation creation to content forgery to cyberattack generation. However, despite the potential for negative socioeconomic impact, generative AI holds tremendous promise in improving the human condition in a large number of ways if created and deployed in a reponsible and trustworthy manner.

Motivated to tackle such challenges and pave the way for positive impact, we have launched GenAI4Good, a global open source initiative for accelerating machine learning for promoting responsible creation and deployment of generative AI for good.  The sub-initiatives that are part of GenAI4Good will be listed and updated in this portal over time as the effort grows.  GenAI4Good is a joint initiative with the [COVID-Net initiative](https://alexswong.github.io/COVID-Net/) and the [Cancer-Net initiative](https://alexswong.github.io/Cancer-Net/).

## AI Illuminated: Generative AI Podcast on the Latest Research Developments 


Podcast: [Click here](https://open.spotify.com/show/5MWM1LvsSGHqagmtp9bdGO?si=4f0725a8de244bd1&nd=1&dlsi=dd8dffcab94b4cda)








## NAS-NeRF: Generative Neural Architecture Search for Neural Radiance Field 


Repo: [Click here](https://saeejithnair.github.io/NAS-NeRF/)


Paper:  [Click here](https://arxiv.org/pdf/2309.14293.pdf)









## DeepfakeArt Challenge Benchmark Dataset for Generative AI Art Forgery and Data Poisoning Detection 


Repo: [Click here](https://github.com/h-aboutalebi/DeepfakeArt)


Benchmark dataset:  [Click here](https://www.kaggle.com/datasets/danielmao2019/deepfakeart)









## MetaGraspNetV2: All-in-One Dataset Enabling Fast and Reliable Robotic Bin Picking via Object Relationship Reasoning and Dexterous Grasping 


Paper: [Click here](https://ieeexplore.ieee.org/document/10309974)


Benchmark dataset:  [Click here](https://github.com/maximiliangilles/MetaGraspNet)










## MetaGraspNet: A Large-Scale Benchmark Dataset for Scene-Aware Ambidextrous Bin Picking via Physics-based Metaverse Synthesis 


Paper: [Click here](https://arxiv.org/pdf/2208.03963.pdf)


Benchmark dataset:  [Click here](https://github.com/maximiliangilles/MetaGraspNet)








## NutritionVerse:  Large-scale Dataset of Real and Synthetic Meal Data for Nutritional Intake Estimation 


Paper: [Click here](https://arxiv.org/abs/2309.07704)


Benchmark dataset:  [Click here](https://www.kaggle.com/nutritionverse/datasets)








## NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation 


Paper: [Click here](https://arxiv.org/abs/2304.05619)


Benchmark dataset:  [Click here](https://www.kaggle.com/datasets/amytai/nutritionverse-3d)








## FoodFusion: A Latent Diffusion Model for Realistic Food Image Generation 


Paper: [Click here](https://arxiv.org/abs/2312.03540)







## ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks 


Paper: [Click here](https://arxiv.org/abs/1811.05817)







## Core GenAI4Good Team

Project Lead: [Alexander Wong](http://www.eng.uwaterloo.ca/~a28wong) ([email protected])

* Hossein Aboutalebi

* Dayou Mao

* Carol Xu

* Amy Tai

* Saeejith Nair

* Yuhao Chen

* Matthew Keller

* Mattie Kerrigan

* Tanisha Nigam

* Komal Vachhani

* Jason Li

* Sriram Kumar

* Cosmo Zhao

* Linlin Xu

* Pengcheng Xi

* Ashkay Ebadi

* Krish Parmar

* Sirisha Rambhatla

* Mohammad Basri

* Helen Chen

**Partners:**