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nerf

Code release for NeRF (Neural Radiance Fields)

neuraltalk

NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

neuraltalk2

Efficient Image Captioning code in Torch, runs on GPU

new-view-synthesis

Collecting papers about new view synthesis

nglod

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes (CVPR 2021 Oral)

normalmapgenerator

Normal Map Generator using python

paddlepaddleexample

百度飞桨示例

pbr-shaders

Standard PBR shader written in Unity Cg

pgmpy

Python Library for Probabilistic Graphical Models

point2mesh

Reconstruct Watertight Meshes from Point Clouds [SIGGRAPH 2020]

pq-net

code for our CVPR 2020 paper "PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes"

principles_of_data_science_chinese

IPython notebooks for "Principles of Data Science" by Sinan Ozdemir, published by Packt.

programming-for-everybody

Chinese Material to Support the Learning

pytorch-iterativefcn

Pytorch implementation of the paper Iterative fully convolutional neural networks for automatic vertebra segmentation accepted in MIDL2018.

pyurgent

Life-long learning for sentiment analysis, supporting Vietnamese and English

qa-survey

北航大数据高精尖中心研究张日崇团队对问答系统的调研。包括知识图谱问答系统（KBQA）和文本问答系统（TextQA），每类系统分别对学术界和工业界进行调研。

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

recognize-named-entities-on-twitter-with-lstms

Recognize named entities with LSTMs

renderlab

App of RTR, PTR and Editor

repwalk

Code and dataset for our paper "Replicate, Walk, and Stop on Syntax: an Effective Neural Network Model for Aspect-Level Sentiment Classification", AAAI2020

research-upon-relationship-between-2019ncov-and-peoples-daily

restaurant

This is Demo For Restaurant Android App.

sdf

Parallelized triangle mesh --> continuous signed distance field on CPU

semi-supervised-lifelong-learning-for-sentiment-classification

Lifelong machine learning is a novel machine learning paradigm which continually learns tasks and accumulates knowledge for reusing. The knowledge extracting and reusing abilities enable the lifelong machine learning to understand the knowledge for solving a task and obtain the ability to solve the related problems. In sentiment classification, traditional approaches like Naïve Bayes focus on the probability for each words with positive or negative sentiment. However, the lifelong machine learning in this paper will investigate this problem in a different angle and attempt to discover which words determine the sentiment of a review. We will pay all attention to obtain knowledge during learning for future learning rather than just solve a current task.

sentibridge

SentiBridge: A Knowledge Base for Entity-Sentiment Representation

simhash

A Python Implementation of Simhash Algorithm

south-african-heart-disease-data-analysis-using-python

Part1 : Data Feature extraction, and visualization using PCA Part 2: Supervised learning: Naive Bayes Classification and logistic regression Part 3: K means clustering and anomaly detection

spine-landmark-detection

Spine Vertebrae Landmark Detection

stl10

Python utilities for reading the STL-10 dataset: http://cs.stanford.edu/~acoates/stl10/

stytr-2

StyTr2 : Image Style Transfer with Transformers