Moving Object Detection
10 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Moving Object Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
RF100
DVSMOTION20
Most implemented papers
Unsupervised Moving Object Detection via Contextual Information Separation
antonilo/unsupervised_detection
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CVPR 2019
We propose an adversarial contextual model for detecting moving objects in images.
Towards Segmenting Anything That Moves
achalddave/segment-any-moving
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To address this concern, we propose two new benchmarks for generic, moving object detection, and show that our model matches top-down methods on common categories, while significantly out-performing both top-down and bottom-up methods on never-before-seen categories.
FMODetect: Robust Detection of Fast Moving Objects
rozumden/FMODetect
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ICCV 2021
Compared to other methods, such as deblatting, the inference is of several orders of magnitude faster and allows applications such as real-time fast moving object detection and retrieval in large video collections.
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.
Moving Object Detection for Event-based Vision using k-means Clustering
Moving object detection is important in computer vision.
Moving Object Detection for Event-based vision using Graph Spectral Clustering
However, these advantages come at a high cost, as the event camera data typically contains more noise and has low resolution.
HM-Net: A Regression Network for Object Center Detection and Tracking on Wide Area Motion Imagery
Wide Area Motion Imagery (WAMI) yields high-resolution images with a large number of extremely small objects.
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
Satellite video cameras can provide continuous observation for a large-scale area, which is important for many remote sensing applications.
RGB-Event Fusion for Moving Object Detection in Autonomous Driving
zzy-zhou/renet
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Moving Object Detection (MOD) is a critical vision task for successfully achieving safe autonomous driving.
RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud
Mobile autonomy relies on the precise perception of dynamic environments.
