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Scene Change Detection

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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.

논문

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Scene Change Detection

논문

EMPLACE: Self-Supervised Urban Scene Change Detection

Robust Scene Change Detection Using Visual Foundation Models and Cross-Attention Mechanisms

ZeroSCD: Zero-Shot Street Scene Change Detection

Towards Generalizable Scene Change Detection

Zero-Shot Scene Change Detection

Unsupervised Change Detection for Space Habitats Using 3D Point Clouds

SeaDSC: A video-based unsupervised method for dynamic scene change detection in unmanned surface vehicles

Industrial Scene Change Detection using Deep Convolutional Neural Networks

Scene Change Detection Using Multiscale Cascade Residual Convolutional Neural Networks

SARAS-Net: Scale and Relation Aware Siamese Network for Change Detection

Differencing based Self-supervised pretraining for Scene Change Detection

How to Reduce Change Detection to Semantic Segmentation

Crowd Source Scene Change Detection and Local Map Update

Shot boundary detection method based on a new extensive dataset and mixed features

City-scale Scene Change Detection using Point Clouds

ChangeSim: Towards End-to-End Online Scene Change Detection in Industrial Indoor Environments

DR-TANet: Dynamic Receptive Temporal Attention Network for Street Scene Change Detection

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection

Epipolar-Guided Deep Object Matching for Scene Change Detection

Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion

Weakly Supervised Silhouette-based Semantic Scene Change Detection

Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection