minygd

Awesome-person-re-identification

Awesome person re-identification

gluon-reid

A code gallery for person re-identification with mxnet-gluon, and I will reproduce many STOA algorithm.

Spatial-Temporal-Re-identification

Spatial-Temporal Re-identification

autumn_2017

杭州电子科技大学 CAMALAB 2017 秋季学期 学习组

awesome-reid-dataset

Collection of public available person re-identification datasets

beyond-part-models

PCB of paper: Beyond Part Models: Person Retrieval with Refined Part Pooling, using Pytorch

Data-Process-KITTI

Data form RGB, depth, disparity to npy

dorn_depth_estimation

Deep Ordinal Regression Network for Monocular Depth Estimation.（在PyTorch上实现CVPR2018论文，深度估计排名第一）

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fastai

The fastai deep learning library, plus lessons and and tutorials

GeoNet_pytorch

An unofficial PyTorch implementation of GeoNet

gluoncv-torch

PyTorch API for GluonCV Models

huxpro.github.io

My Blog / Jekyll Themes / PWA

KITTI_Tutorial

Tutorial for using Kitti dataset easily

minygd.github.io

Detect & Description.

Monocular-Depth-Estimation-using-modified-PSPNet

Muse-CGH

Stylish Computer Generated Handwritings

One-Example-Person-ReID

Code for TIP2019 Progressive Learning for Person Re-Identification with One Example

panorama

Image alignment and stitching with MATLAB

panoramic-depth-estimation

Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery

part_reid

Code for ICCV2017 paper: Deeply-Learned Part-Aligned Representations for Person Re-Identification

PCB_RPP_for_reID

person-reid-triplet-loss-baseline

Rank-1 89% (Single Query) on Market1501 with raw triplet loss, In Defense of the Triplet Loss for Person Re-Identification, using Pytorch

pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

pytorch-exercise

Practical Exercise Codes for PyTorch

region-conv

Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade

sparse-to-dense

ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (Torch Implementation)

SphereNet-pytorch

Stanford-CS229-CN

斯坦福大学CS229CN讲义部分的翻译（CS229 Chinese Edition）

Synthetic2Realistic

ECCV 2018 "T2Net: Synthetic-to-Realistic Translation for Depth Estimation Tasks"