We introduce an efficient video segmentation system for resource-limited edge devices leveraging heterogeneous compute.
no code implementations • 23 Jun 2022 • Ivan Grishchenko, Valentin Bazarevsky, Andrei Zanfir, Eduard Gabriel Bazavan, Mihai Zanfir, Richard Yee, Karthik Raveendran, Matsvei Zhdanovich, Matthias Grundmann, Cristian Sminchisescu
We present BlazePose GHUM Holistic, a lightweight neural network pipeline for 3D human body landmarks and pose estimation, specifically tailored to real-time on-device inference.
We present an on-device real-time hand gesture recognition (HGR) system, which detects a set of predefined static gestures from a single RGB camera.
Thus, the number of unreachable peers can only be estimated based on some indicators.
Cryptography and Security Networking and Internet Architecture
3D object detection has recently become popular due to many applications in robotics, augmented reality, autonomy, and image retrieval.
Ranked #2 on Monocular 3D Object Detection on Google Objectron
Our tracker is capable of performing relative-scale 9-DoF tracking in real-time on mobile devices.
We present Attention Mesh, a lightweight architecture for 3D face mesh prediction that uses attention to semantically meaningful regions.
We present a real-time on-device hand tracking pipeline that predicts hand skeleton from single RGB camera for AR/VR applications.
We present BlazePose, a lightweight convolutional neural network architecture for human pose estimation that is tailored for real-time inference on mobile devices.
Ranked #1 on 3D Pose Estimation on Google-Yoga
The former is used when there is only pose supervision, and the latter is for the case when shape supervision is available, even a weak one.
Ranked #3 on Monocular 3D Object Detection on Google Objectron
We present BlazeFace, a lightweight and well-performing face detector tailored for mobile GPU inference.
On-device inference of machine learning models for mobile phones is desirable due to its lower latency and increased privacy.
2 code implementations • 14 Jun 2019 • Camillo Lugaresi, Jiuqiang Tang, Hadon Nash, Chris McClanahan, Esha Uboweja, Michael Hays, Fan Zhang, Chuo-Ling Chang, Ming Guang Yong, Juhyun Lee, Wan-Teh Chang, Wei Hua, Manfred Georg, Matthias Grundmann
A developer can use MediaPipe to build prototypes by combining existing perception components, to advance them to polished cross-platform applications and measure system performance and resource consumption on target platforms.
Distributed, Parallel, and Cluster Computing
Our proposed framework provides an efficient approach for finding temporally consistent occlusion boundaries in video by utilizing causality, redundancy in videos, and semantic layout of the scene.