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

No papers found.

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