An example of how to adapt the C3D CNN for another problem. Really a fork of https://github.com/axon-research/c3d-keras
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Updated
Sep 27, 2017 - Python
An example of how to adapt the C3D CNN for another problem. Really a fork of https://github.com/axon-research/c3d-keras
Internship in Computer Vision Lab at University of Louisville
STEP: Spatio-Temporal Progressive Learning for Video Action Detection. CVPR'19 (Oral)
Acquire users location in android with ease, detect movement, geofence areas of interest, geocode users location
ML application on wearable devices to predict a person's activities.
Code for our CVPR 2021 paper "Coarse-Fine Networks for Temporal Activity Detection in Videos"
2-layer neural network that predicts exercise activity through IMU sensor data. For the graduate course "Introduction to Optimization and Machine Learning" at SJSU. Project partners, Antonio Cervantes and Christian Pedrigal.
This model detects workers' productivity states, using motion signals generated by the accelerometer embedded in the three mounted receiving beacons.
[BMVC 2021]: Official PyTorch implementation of : "Few Shot Temporal Action Localization using Query Adaptive Transformers"
Out-of-the-box code and models for CMU's object detection and tracking system for multi-camera surveillance videos. Speed optimized Faster-RCNN model. Tensorflow based. Also supports EfficientDet. WACVW'20
End-to-End Semi-Supervised Learning for Video Action Detection [CVPR 2022]
Activity Detection Using Unsupervised Learning Algorithms: DBSCAN, K-Means & Spectral Clustering to identify and label different activities in a dataset
An advanced system integrating RFID, facial recognition, and AI-based activity detection to enhance campus safety
Activity and Sequence Detection Evaluation Metrics: A package to evaluate activity detection results, including the sequence of events given multiple activity types.
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