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
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Dec 16, 2022 - Python
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
STEP: Spatio-Temporal Progressive Learning for Video Action Detection. CVPR'19 (Oral)
Code for our CVPR 2021 paper "Coarse-Fine Networks for Temporal Activity Detection in Videos"
[CVPR 2022] End-to-End Semi-Supervised Learning for Video Action Detection
[BMVC 2021]: Official PyTorch implementation of : "Few Shot Temporal Action Localization using Query Adaptive Transformers"
An example of how to adapt the C3D CNN for another problem. Really a fork of https://github.com/axon-research/c3d-keras
Acquire users location in android with ease, detect movement, geofence areas of interest, geocode users location
Activity Detection Using Unsupervised Learning Algorithms: DBSCAN, K-Means & Spectral Clustering to identify and label different activities in a dataset
Simple stair (and movement) detection for Android
Internship in Computer Vision Lab at University of Louisville
Generate complex event processing (Siddhi) activity detection apps based on IoT data and expert annotations.
ML application on wearable devices to predict a person's activities.
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.
A web-based project monitoring system integrating YOLO and Reinforcement Learning for real-time activity detection and decision-making.
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.
VisionSafe - AI powered safe vs unsafe activity detection system using YOLOv8 and Flask with a React dashboard.
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