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Trending Technology's Projects

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Semi-supervised Video Deraining with Dynamical Rain Generator (CVPR, 2021, Pytorch)

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Skull stripping and brain tissue segmentation

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Playing videos through S3 buckets (Wasabi, AWS, etc.) through client-side VideoJS player

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Publicly Open Amazon AWS S3 Bucket Viewer

sa-autoaug icon sa-autoaug

Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

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ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

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CLI search and replace | Space Age seD

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[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction

saferwall icon saferwall

A hackable malware sandbox for the 21st Century

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SqlAlchemy Flask-Restful Swagger Json:API OpenAPI

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A hackable programming language I'm working on. Currently WIP.

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The universal proxy toolchain for Android

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A simple easy to use Flutter DApp , which keeps a track of all your day to day transactions by using Ethereum blockchain in the background which in turn increases your credit score.

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A vision library for performing sliced inference on large images/small objects

saic_depth_completion icon saic_depth_completion

Official implementation of "Decoder Modulation for Indoor Depth Completion" https://arxiv.org/abs/2005.08607

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⛵️ A React library for Solana account management and transaction processing.

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The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

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🌸 Sakura Userbot 🌸 is a plugable telegram userbot project made in python based on telethon.

salad icon salad

SALaD (Semi-Automatic Landslide Detection) is a landslide mapping system. SALaD utilizes Object-based Image Analysis and Random Forest to map landslides. It requires optical imagery, a DEM, corner coordinates of a training area, and manually mapped landslides within the training area. The code is built to run primarily on a Linux.

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A modular, high performance, headless e-commerce platform built with Python, GraphQL, Django, and React.

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Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving

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