Jialin Yuan's repositories

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omni3d-box

Code release for "Omni3D A Large Benchmark and Model for 3D Object Detection in the Wild"

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Leetcode-oral

leetcode record

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GWAS-Root-analysis

segment of plant and compute traits

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vimrc

The ultimate Vim configuration (vimrc)

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SOLO

SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.

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2020-instanceSeg

Deep Variational Instance Segmentation

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pytorch-meta

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

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TensorBoard-guidance

Introduction about how to create log-file visualizing in TensorBoard in different framework

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TensorFlow-Examples

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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Keras-GAN

Keras implementations of Generative Adversarial Networks.

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pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

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pytorch-CycleGAN-and-pix2pix

Image-to-image translation in PyTorch (e.g., horse2zebra, edges2cats, and more)

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keras-deeplab-v3-plus

Keras implementation of Deeplab v3+ with pretrained weights

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summary

learning materials summary, including blogs, authors, papers, conference, etc..

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focal-loss

Tensorflow version implementation of focal loss for binary and multi classification

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models

Models and examples built with TensorFlow

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pytorch-semantic-segmentation

PyTorch for Semantic Segmentation

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myCplusplusModules

Including useful basic implementation in Image/Video Processing domain.

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FilePreprocess

Implementation of some basic preprocess over image dataset, to generate input for different model. like:

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tensorflow-deeplab-resnet

DeepLab-ResNet rebuilt in TensorFlow

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bayes-nn

Lecture notes on Bayesian deep learning

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self-driving-car

Udacity Self-Driving Car Engineer Nanodegree projects.

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The-Art-Of-Programming-By-July

本项目曾冲到全球第一,干货集锦见本页面最底部,另完整精致的纸质版《编程之法:面试和算法心得》已在京东/当当上销售

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LinuxTool

Linux下常用工具及其命令介绍

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FCIS

Fully Convolutional Instance-aware Semantic Segmentation

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pydensecrf

Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

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