Motion Detection
19 papers with code • 1 benchmarks • 2 datasets
Motion Detection is a process to detect the presence of any moving entity in an area of interest. Motion Detection is of great importance due to its application in various areas such as surveillance and security, smart homes, and health monitoring.
Source: Different Approaches for Human Activity Recognition– A Survey
Benchmarks
These leaderboards are used to track progress in Motion Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
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nuScenes
KITTI'15 MSplus
Most implemented papers
A Robust Road Vanishing Point Detection Adapted to the Real-World Driving Scenes
The experimental results show that the proposed method outperforms the existing motion-based and edge-based road VP detection methods for various illumination conditioned driving scenes.
UAV Images Dataset for Moving Object Detection from Moving Cameras
The problem of recognizing moving objects from aerial images is one of the important issues in computer vision.
Motion Detection using CSI from Raspberry Pi 4
This system exploits the correlation between CSI frames, on which we perform variance analysis using our algorithm to accurately measure the full period of a resident's movement.
Optical Flow Based Motion Detection for Autonomous Driving
kamanphoebe/motiondetection
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Motion detection is a fundamental but challenging task for autonomous driving.
Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections
xxh43/ukmd
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We operationalize this concept with an algorithm that optimizes a shape's part motion parameters such that it can transform into other shapes in the collection.
Learning heterogeneous delays in a layer of spiking neurons for fast motion detection
In this study, we present a model designed to efficiently detect temporal spiking motifs using a layer of spiking neurons equipped with heterogeneous synaptic delays.
EGVD: Event-Guided Video Deraining
booker-max/egvd
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In this paper, we approach video deraining by employing an event camera.
Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow
cv-stuttgart/detectiondefenses
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In this paper, we thoroughly examine the currently available detect-and-remove defenses ILP and LGS for a wide selection of state-of-the-art optical flow methods, and illuminate their side effects on the quality and robustness of the final flow predictions.
Event-Based Motion Magnification
ZhengPeng7/motion_magnification_learning-based
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Detecting and magnifying imperceptible high-frequency motions in real-world scenarios has substantial implications for industrial and medical applications.
