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6dpose

implement some algorithms of 6d pose estimation

a-pytorch-tutorial-to-object-detection

SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection

actiondetection-dbg

affectnet

ai-challenger-keypoints-pytorch

AI Challenger Keypoints Detection(https://challenger.ai/competition/keypoint/leaderboard) (SYSU_Pose Rank #5)

android_mediacodec_surface_example

in this example, I will show you how to play video using MediaCodec together with SurfaceView, GLSurfaceView and TextureView

android_mediacodectest

MediaCodec API sample app. (Video recording with effect)

androidopenglvideodemo

Demo of using TextureView and OpenGL on it to render video

apc

aubo_robot

Developed for aubo robot (http://www.aubo-robotics.cn/)

awesome-6d-pose-estimation

6D pose estimation algorithm

awesome-object-pose

This repository is a curated list of papers and open source code for 6D Object Pose Estimation.

book-code

《深度学习之PyTorch实战计算机视觉》全书代码

caffe

Caffe: a fast open framework for deep learning.

caffe2

Caffe2 is a lightweight, modular, and scalable deep learning framework.

camera-samples

Multiple samples showing the best practices in camera APIs on Android.

cameraxtutorial

CameraX sample app written in Java

centernet

Object detection, 3D detection, and pose estimation using center point detection:

centernet-1

Codes for our paper "CenterNet: Keypoint Triplets for Object Detection" .

ceres-solver

A large scale non-linear optimization library

cocoapi

COCO API - Dataset @ http://cocodataset.org/

compose-samples

Official Jetpack Compose samples.

conversion-and-coding-implementation-for-hdr-video-with-pq-transfer-characteristics

The high brightness and dark parts of videos are compressed and lost during the transmitting by the traditional standard dynamic range (SDR). The high dynamic range (HDR) has gained more and more attention, because it can faithfully restore the high brightness and dark parts of grayscale and color level. In order to realize the conversion and coding of HDR of videos, a PQ codec is written on the basis of H.265 in C language and the functions of pre-coding and post-decoding are added. The pre-coding process is divided into Perceptual Quantization (PQ) curve photoelectric conversion, RGB and YCbCr mutual conversion, quantification, sampling. The post-decoding process is inverse process of pre-coded, which includes upper sampling, anti-quantization, color space conversion, perceptual quantification. The core of codec is to use the PQ curve to transform the optical signal into electrical signal nonlinearly, thus expanding the dynamic reproduction range of the traditional transmission system. Finally, decoding videos can realize the whole brightness dynamic range, which is visible to the human eye.

cornernet-lite

cs229

dacon

remove glare 去除炫光

data

PCD files for tutorials, examples, or PCL-related applications

dbow3

Improved version of DBow2

deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

deepgamingai_fifa

A deep learning based AI bot for playing the football simulation game FIFA 18 (Windows platform)