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MoFaNeRF: Morphable Facial Neural Radiance Field
A PyTorch re-implementation of Neural Radiance Fields
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
An arctic, north-bluish clean and elegant iTerm2 color scheme.
Deflecting Adversarial Attacks with Pixel Deflection
Project for 10-805: Machine Learning for large datasets
10605 group 8 spring 2020
Final Project for 10-605: ML with Large Datasets
CMU 16833 Homework and projects
SALSA: Semantic Assisted Life-Long SLAM for Indoor Environments (16-833 SLAM Project at CMU)
This project is concerned with the automatic detection and analysis of work zones (construction zones) in naturalistic roadway images. An underlying motivation is to identify locations that may pose challenges to advanced driver-assistance systems or autonomous vehicle navigation systems. We first present an in-depth characterization of work zone scenes from a custom dataset collected from more than a million miles of naturalistic driving data. Then we describe two ML algorithms based on the ResNet and U-Net architectures. The first approach works in an image classification framework that classifies an image as a work zone scene or non-work zone scene. The second algorithm was developed to identify individual components representing evidence of a work zone (signs, barriers, machines, etc.). These systems achieved an F{0.5} score of 0.951 for the classification task and an F1 score of 0.611 for the segmentation task. We further demonstrate the viability of our proposed models through salience map analysis and ablation studies. To our knowledge, this is the first study to consider the detection of work zones in large-scale naturalistic data. The systems demonstrate potential for real-time detection of construction zones using forward-looking cameras mounted on automobiles.
Fully automated provisioning of AWS EC2 Spot Instances for Deep Learning workloads using Terraform.
Homework for Deep Unsupervised Learning (CS294-158) course
Assignments for CMU 16-824 Visual Learning and Recognition
VQA assignment for course 16824
Implementation of Weakly Supervised Deep Detection Networks using the latest version of PyTorch
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.