Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
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Updated
May 3, 2024 - Python
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
A deep learning framework for multi-animal pose tracking.
a toolkit for pose estimation using deep learning
Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.
Behavioral Observation Research Interactive Software
Motion Planner for Self Driving Cars
Variational Animal Motion Embedding - A tool for time series embedding and clustering
live, low-latency markerless multi-camera 3D animal tracking system
Use iterative feature pruning to identify hierarchical clusters.
Closed-loop behavioral experiment toolkit using pose estimation of body parts.
WormPose: Image synthesis and convolutional networks for pose estimation in C. elegans
Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs
Crowd behavior analysis is an important field of research in modern world. It has wide applications in surveillance and public safety which are one of the prime social concerns. One way to analyze crowd behavior is obtain crowd movement data and then find out outliers in the individual trajectories to infer any abnormal behavior in the crowd.
SIPEC: the deep-learning Swiss knife for behavioral data analysis
Headless DeepLabCut (no GUI support)
Code for the ECCV'22 paper "Geometric Features Informed Multi-person Human-object Interaction Recognition in Videos".
Fully automated (rodent) limb motion analysis toolbox for behavioral analysis with bodypart coordinate data, building upon markerless pose estimation.
2020新网银行金融科技挑战赛 AI算法赛道A榜14, B榜16解决方案
Collection of scripts that utilize Twitter API for suspicious behavior analysis
Network behavior discovery and behavioral profile generation. https://link.springer.com/chapter/10.1007/978-3-030-62582-5_15
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