wujiqa's Stars
facebookresearch/SlowFast
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
ShengxiLi/oba_scheme
Telecommunication-Telemedia-Assessment/SITI
Command-line tool for calculating Spatial Information / Temporal Information according to ITU-T P.910
fraunhoferhhi/vvenc
VVenC, the Fraunhofer Versatile Video Encoder
TencentCloud/O266player
0voice/audio_video_streaming
音视频流媒体权威资料整理,500+份文章,论文,视频,实践项目,协议,业界大神名单。
virinext/hevcesbrowser
HEVCESBrowser is a tool for analyzing hevc(h265) bitstreams
biaominhk/GitlHEVCAnalyzer
Gitl HEVC/H.265 Analyzer based on Qt. Custom filters supported.
Telecommunication-Telemedia-Assessment/bitstream_mode3_videoparser
Open source video parser for the ITU-T P.1204.3 model.
cd-athena/VCA
Video complexity analyzer
facebookresearch/mae
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
MCG-NJU/VideoMAE
[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
jindongwang/MachineLearning
一些关于机器学习的学习资料与研究介绍
plantsgo/ijcai-2018
ijcai-2018 top1 solution
sunwei925/SimpleVQA
A Deep Learning based No-reference Quality Assessment Model for UGC Videos
IENT/YUView
The Free and Open Source Cross Platform YUV Viewer with an advanced analytics toolset
lucidrains/vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
OpenGVLab/UniFormerV2
[ICCV2023] UniFormerV2: Spatiotemporal Learning by Arming Image ViTs with Video UniFormer
Netflix/vmaf
Perceptual video quality assessment based on multi-method fusion.
dingkeyan93/IQA-optimization
Comparison of IQA models in Perceptual Optimization
minivision-ai/Silent-Face-Anti-Spoofing
静默活体检测(Silent-Face-Anti-Spoofing)
youngxiao/SVM-demo
mikhailiuk/pytorch-fsim
Differentiable implementation of the Feature Similarity Index Measure in Pytorch
nekhtiari/image-similarity-measures
:chart_with_upwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
pranjaldatta/SSIM-PyTorch
A PyTorch based Implementation of Structural Similarity Index. Wriiten along with a companion blog.
Po-Hsun-Su/pytorch-ssim
pytorch structural similarity (SSIM) loss
jorge-pessoa/pytorch-msssim
PyTorch differentiable Multi-Scale Structural Similarity (MS-SSIM) loss
idealo/image-quality-assessment
Convolutional Neural Networks to predict the aesthetic and technical quality of images.