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Found 8 papers, 5 papers with code
Blendshapes GHUM: Real-time Monocular Facial Blendshape Prediction
We present Blendshapes GHUM, an on-device ML pipeline that predicts 52 facial blendshape coefficients at 30+ FPS on modern mobile phones, from a single monocular RGB image and enables facial motion capture applications like virtual avatars.
Efficient Heterogeneous Video Segmentation at the Edge
We introduce an efficient video segmentation system for resource-limited edge devices leveraging heterogeneous compute.
BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation
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.
Attention Mesh: High-fidelity Face Mesh Prediction in Real-time
We present Attention Mesh, a lightweight architecture for 3D face mesh prediction that uses attention to semantically meaningful regions.
Real-time Pupil Tracking from Monocular Video for Digital Puppetry
We present a simple, real-time approach for pupil tracking from live video on mobile devices.
BlazePose: On-device Real-time Body Pose tracking
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
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
We present BlazeFace, a lightweight and well-performing face detector tailored for mobile GPU inference.
Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
We propose 4 insights that help to significantly improve the performance of deep learning models that predict surface normals and semantic labels from a single RGB image.
Ranked #1 on
Semantic Segmentation
on ScanNetV2
(Pixel Accuracy metric)
