Motion Capture
State-of-the-art leaderboards
Greatest papers with code
Hand Keypoint Detection in Single Images using Multiview Bootstrapping
CVPR 2017
• CMU-Perceptual-Computing-Lab/openpose
• 
The method is used to train a hand keypoint detector for single images.
Generative Choreography using Deep Learning
Recent advances in deep learning have enabled the extraction of high-level features from raw sensor data which has opened up new possibilities in many different fields, including computer generated choreography.
Neural Relational Inference for Interacting Systems
Interacting systems are prevalent in nature, from dynamical systems in physics to complex societal dynamics.
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.
Monocular Total Capture: Posing Face, Body, and Hands in the Wild
CVPR 2019
• CMU-Perceptual-Computing-Lab/MonocularTotalCapture
• 
We present the first method to capture the 3D total motion of a target person from a monocular view input.
3D HUMAN POSE ESTIMATION HAND POSE ESTIMATION MOTION CAPTURE
The Blackbird Dataset: A large-scale dataset for UAV perception in aggressive flight
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 $7. 0ms^-1$.
The TUM VI Benchmark for Evaluating Visual-Inertial Odometry
• VladyslavUsenko/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.
Learning Human Optical Flow
Given this, we devise an optical flow algorithm specifically for human motion and show that it is superior to generic flow methods.
The Event-Camera Dataset and Simulator: Event-based Data for Pose Estimation, Visual Odometry, and SLAM
New vision sensors, such as the Dynamic and Active-pixel Vision sensor (DAVIS), incorporate a conventional global-shutter camera and an event-based sensor in the same pixel array.
MOTION CAPTURE MOTION ESTIMATION POSE ESTIMATION VISUAL ODOMETRY
Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning
• Samarth-Tripathi/IEMOCAP-Emotion-Detection
Emotion recognition has become an important field of research in Human Computer Interactions as we improve upon the techniques for modelling the various aspects of behaviour.