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Name: Avani Gupta

Type: User

Company: IIIT Hyderabad

Bio: G42 Healthcare, Abu Dhabi | Masters @CVIT IIIT H | Responsible AI | Presented Masters Work @Neurips 2023 | Research Intern @IBM

Twitter: Avani_Gupta__

Location: Abu Dhabi

Blog: https://avani17101.github.io/

Hello there 👋, I am Avani. Welcome to my github 🌠

💁 About me Please refer to my Website for updated information about me.

🎯 My skills

ML interpretability
Computer vision
Computer graphics
Deep Learning
Re-inforcement learning
NLP
Artificial Intelligence
Web and app developemnt (Flask, Django, Flutter, SQL, MERN stack, Javascript and more..)
Fine arts too 😉

Some of presentations I did as part of 3D Vision Induction workshop at CVIT:
NeRF: Neural Radiance Fields
GANs (Felicity's ML workshop and 3D Vision Workshop)

I am passionate on building real-life applications for solving problems faced by people worldwide.

📫 Linkedin
🌀 Website
🔵 Twitter
📧 [email protected], [email protected]

Do checkout my latest project for TreeHacks(Hackathon by Stanford) DataSynth
Have fun exploring my projects. 😎
Some stats 😉

Avani Gupta's Projects

3d-bonet

🔥3D-BoNet in Tensorflow (NeurIPS 2019, Spotlight)

3d-computer-vision-workshop

3D computer vision workshop at CVIT IIIT H

3d-game-shaders-for-beginners

🎮 A step-by-step guide to implementing SSAO, depth of field, lighting, normal mapping, and more for your 3D game.

3d-ken-burns

an implementation of 3D Ken Burns Effect from a Single Image using PyTorch

3d-photo-inpainting

[CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting

3d-r2n2

Single/multi view image(s) to voxel reconstruction using a recurrent neural network

3d-shape-analysis-paper-list

A list of recent papers, libraries and datasets about 3D shape/geometry analysis (by topics, updating).

3d-vae-gan

an tensorflow implemention of 3D-VAE-GAN for single image 3D reconstruction

3dv_tutorial

An Invitation to 3D Vision: A Tutorial for Everyone

ace

Towards Automatic Concept-based Explanations

ace_tcav_pytorch

Automatic Concept Extraction and TCAV Implemented in Pytorch

adversarial-neural-crypto

Adversarial Neural Cryptography implementations

adversarial-neural-cryptography

An implementation of the ICLR 2017 paper 'Learning to Protect Communications with Adversarial Neural Cryptography' while extending it in trying new models and testing it against more sophisticated networks.