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Abdullah Hamdi's Projects

3d-pose-baseline icon 3d-pose-baseline

A simple baseline for 3d human pose estimation in tensorflow. To be presented at ICCV 17.

3d-sdn icon 3d-sdn

[NeurIPS 2018] 3D-Aware Scene Manipulation via Inverse Graphics

advpc icon advpc

AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds (ECCV 2020)

ai_snake icon ai_snake

AI snake game , based on SDL2 Library C++ .Intelligent snake game with jumping feature , AI algorithm implemented on opponent snakes

awesome-mvdl icon awesome-mvdl

awesome list of multi-view deep learning papers for 3D understanding and generation

blogposts icon blogposts

here you can find all supplemental material to my blog posts

closerlook3d icon closerlook3d

A Closer Look at Local Aggregation Operators in Point Cloud Analysis(ECCV 2020)

dcgan-tensorflow icon dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

ges-splatting icon ges-splatting

Original reference implementation of "GES : Generalized Exponential Splatting for Efficient Radiance Field Rendering" [CVPR 2024]

mvtn icon mvtn

pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"

mvtorch icon mvtorch

a Pytorch library for multi-view 3D understanding and generation

pix2pixhd icon pix2pixhd

Synthesizing and manipulating 2048x1024 images with conditional GANs

pix4point icon pix4point

Official Repo for paper `Pix4Point: Image Pretrained Transformers for 3D Point Cloud Understanding`

pointnext icon pointnext

[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

sada icon sada

SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications (AAAI 2020)

saudioss icon saudioss

قائمة بالمشاريع السعودية المفتوحة المصدر

scrapeasy icon scrapeasy

Scraping in python made easy - receive the content you like in just one line of code

semantic-robustness icon semantic-robustness

implementation of the paper: "Towards Analyzing Semantic Robustness of Deep Neural Networks" (ECCV 2020 workshop)

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