Foreground Segmentation
25 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Foreground Segmentation
Most implemented papers
One-Shot Video Object Segmentation
kmaninis/OSVOS-PyTorch
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CVPR 2017
This paper tackles the task of semi-supervised video object segmentation, i. e., the separation of an object from the background in a video, given the mask of the first frame.
Neural Head Reenactment with Latent Pose Descriptors
shrubb/latent-pose-reenactment
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CVPR 2020
We propose a neural head reenactment system, which is driven by a latent pose representation and is capable of predicting the foreground segmentation alongside the RGB image.
Explicit Visual Prompting for Universal Foreground Segmentations
nifangbaage/explicit-visual-prompt
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We take inspiration from the widely-used pre-training and then prompt tuning protocols in NLP and propose a new visual prompting model, named Explicit Visual Prompting (EVP).
PartSTAD: 2D-to-3D Part Segmentation Task Adaptation
KAIST-Visual-AI-Group/PartSTAD
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Our proposed task adaptation method finetunes a 2D bounding box prediction model with an objective function for 3D segmentation.
Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding
Our network takes an RGB image in three different scales and produces a foreground segmentation probability mask for the corresponding image.
One-Shot Segmentation in Clutter
michaelisc/cluttered-omniglot
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ICML 2018
We tackle the problem of one-shot segmentation: finding and segmenting a previously unseen object in a cluttered scene based on a single instruction example.
Learning Multi-scale Features for Foreground Segmentation
Foreground segmentation algorithms aim segmenting moving objects from the background in a robust way under various challenging scenarios.
Online Mutual Foreground Segmentation for Multispectral Stereo Videos
The segmentation of video sequences into foreground and background regions is a low-level process commonly used in video content analysis and smart surveillance applications.
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.
"What's This?" -- Learning to Segment Unknown Objects from Manipulation Sequences
Furthermore, while the motion of the manipulator and the object are substantial cues for our algorithm, we present means to robustly deal with distraction objects moving in the background, as well as with completely static scenes.
