Video Background Subtraction
5 papers with code • 13 benchmarks • 0 datasets
These leaderboards are used to track progress in Video Background Subtraction
Most implemented papers
Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction
We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements.
Robust Graph Learning from Noisy Data
The proposed model is able to boost the performance of data clustering, semisupervised classification, and data recovery significantly, primarily due to two key factors: 1) enhanced low-rank recovery by exploiting the graph smoothness assumption, 2) improved graph construction by exploiting clean data recovered by robust PCA.
Illumination-Based Data Augmentation for Robust Background Subtraction
A core challenge in background subtraction (BGS) is handling videos with sudden illumination changes in consecutive frames.
Autoencoder-based background reconstruction and foreground segmentation with background noise estimation
The main novelty of the proposed model is that the autoencoder is also trained to predict the background noise, which allows to compute for each frame a pixel-dependent threshold to perform the foreground segmentation.
A Deep Moving-camera Background Model
Moreover, existing MCBMs usually model the background either on the domain of a typically-large panoramic image or in an online fashion.