SOTAVerified

Scene Change Detection

Scene change detection (SCD) refers to the task of localizing changes and identifying change-categories given two scenes. A scene can be either an RGB (+D) image or a 3D reconstruction (point cloud). If the scene is an image, SCD is a form of pixel-level prediction because each pixel in the image is classified according to a category. On the other hand, if the scene is point cloud, SCD is a form of point-level prediction because each point in the cloud is classified according to a category.

Some example benchmarks for this task are VL-CMU-CD, PCD, and CD2014. Recently, more complicated benchmarks such as ChangeSim, HDMap, and Mallscape are released.

Models are usually evaluated with the Mean Intersection-Over-Union (Mean IoU), Pixel Accuracy, or F1 metrics.

Papers

Showing 2125 of 25 papers

TitleStatusHype
Hierarchical Paired Channel Fusion Network for Street Scene Change Detection0
Industrial Scene Change Detection using Deep Convolutional Neural Networks0
City-scale Scene Change Detection using Point Clouds0
A Category Agnostic Model for Visual Rearrangment0
ZeroSCD: Zero-Shot Street Scene Change Detection0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1C-3POCategory mIoU27.8Unverified
2RTABMAP+CSCDNetCategory mIoU26.1Unverified
3RTABMAP+ChangeNetCategory mIoU23Unverified
#ModelMetricClaimedVerifiedStatus
1C-3PO (VGG-16)F1-score0.83Unverified
2C-3PO (ResNet-18)F1-score0.82Unverified
#ModelMetricClaimedVerifiedStatus
1Robust-Scene-Change-Detection (Diff-View Augmentation)F1-score0.78Unverified
2Robust-Scene-Change-DetectionF1-score0.74Unverified
#ModelMetricClaimedVerifiedStatus
1C-3PO (VGG-16)F1-score0.8Unverified
2C-3PO (ResNet-18)F1-score0.79Unverified
#ModelMetricClaimedVerifiedStatus
1GeSCF (zero-shot)F1 score58.2Unverified
#ModelMetricClaimedVerifiedStatus
1Demo_SCDOMQ0.02Unverified