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Motion Capture

52 papers with code · Computer Vision

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XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera

1 Jul 2019osmr/imgclsmob

The first stage is a convolutional neural network (CNN) that estimates 2D and 3D pose features along with identity assignments for all visible joints of all individuals. We contribute a new architecture for this CNN, called SelecSLS Net, that uses novel selective long and short range skip connections to improve the information flow allowing for a drastically faster network without compromising accuracy.

3D HUMAN POSE ESTIMATION MOTION CAPTURE

Neural Relational Inference for Interacting Systems

ICML 2018 ethanfetaya/nri

Interacting systems are prevalent in nature, from dynamical systems in physics to complex societal dynamics.

MOTION CAPTURE

Learning from Synthetic Humans

CVPR 2017 gulvarol/surreal

In this work we present SURREAL (Synthetic hUmans foR REAL tasks): a new large-scale dataset with synthetically-generated but realistic images of people rendered from 3D sequences of human motion capture data.

3D HUMAN POSE ESTIMATION HUMAN PART SEGMENTATION MOTION CAPTURE

Skeleton-Aware Networks for Deep Motion Retargeting

12 May 2020DeepMotionEditing/deep-motion-editing

In other words, our operators form the building blocks of a new deep motion processing framework that embeds the motion into a common latent space, shared by a collection of homeomorphic skeletons.

MOTION CAPTURE MOTION RETARGETING MOTION SYNTHESIS

Monocular Real-time Hand Shape and Motion Capture using Multi-modal Data

CVPR 2020 CalciferZh/minimal-hand

We present a novel method for monocular hand shape and pose estimation at unprecedented runtime performance of 100fps and at state-of-the-art accuracy.

MOTION CAPTURE POSE ESTIMATION

The TUM VI Benchmark for Evaluating Visual-Inertial Odometry

17 Apr 2018VladyslavUsenko/basalt-mirror

For trajectory evaluation, we also provide accurate pose ground truth from a motion capture system at high frequency (120 Hz) at the start and end of the sequences which we accurately aligned with the camera and IMU measurements.

MOTION CAPTURE VISUAL ODOMETRY

The Blackbird Dataset: A large-scale dataset for UAV perception in aggressive flight

3 Oct 2018mit-fast/FlightGoggles

The Blackbird unmanned aerial vehicle (UAV) dataset is a large-scale, aggressive indoor flight dataset collected using a custom-built quadrotor platform for use in evaluation of agile perception. Inspired by the potential of future high-speed fully-autonomous drone racing, the Blackbird dataset contains over 10 hours of flight data from 168 flights over 17 flight trajectories and 5 environments at velocities up to $7. 0ms^-1$.

MOTION CAPTURE