michalolejniczak Goto Github PK

as-gcn

The model architecture of AS-GCN (for human action recognition)

classifiershog

courses

fast.ai Courses

docker-cassandra

Cassandra in Docker with fast startup

fpinscala

Code, exercises, answers, and hints to go along with the book "Functional Programming in Scala"

play-samples

priam

Co-Process for backup/recovery, Token Management, and Centralized Configuration management for Cassandra.

sonar-github

SonarQube GitHub Plugin

squeezenet_demo

swagger-editor

Swagger Editor

swagger-ui

Swagger UI is a collection of HTML, Javascript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.

templete

templete

tensorflow

Computation using data flow graphs for scalable machine learning

unik

Official implementation of our paper "A Unified Framework for Real-world Skeleton-based Action Recognition" on Toyota Smarthome/Penn Action/NTU-RGB+D/Posetics datasets

unipose

We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.

vanilla-yolo-keras

visioon_pack

Visioon_pack