Video Object Segmentation
243 papers with code • 9 benchmarks • 17 datasets
Video object segmentation is a binary labeling problem aiming to separate foreground object(s) from the background region of a video.
For leaderboards please refer to the different subtasks.
Benchmarks
These leaderboards are used to track progress in Video Object Segmentation
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Libraries
Use these libraries to find Video Object Segmentation models and implementationsDatasets
DAVIS
DAVIS 2017
DAVIS 2016
YouTube-VOS 2018
FBMS
SegTrack-v2
Referring Expressions for DAVIS 2016 & 2017
MOSE
BL30K
LVOS
Subtasks
Most implemented papers
Fast Video Object Segmentation by Reference-Guided Mask Propagation
seoungwugoh/RGMP
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CVPR 2018
We validate our method on four benchmark sets that cover single and multiple object segmentation.
Tukey-Inspired Video Object Segmentation
We investigate the problem of strictly unsupervised video object segmentation, i. e., the separation of a primary object from background in video without a user-provided object mask or any training on an annotated dataset.
RANet: Ranking Attention Network for Fast Video Object Segmentation
Specifically, to integrate the insights of matching based and propagation based methods, we employ an encoder-decoder framework to learn pixel-level similarity and segmentation in an end-to-end manner.
MAST: A Memory-Augmented Self-supervised Tracker
zlai0/MAST
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CVPR 2020
Recent interest in self-supervised dense tracking has yielded rapid progress, but performance still remains far from supervised methods.
Learning Fast and Robust Target Models for Video Object Segmentation
andr345/frtm-vos
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CVPR 2020
The target appearance model consists of a light-weight module, which is learned during the inference stage using fast optimization techniques to predict a coarse but robust target segmentation.
Collaborative Video Object Segmentation by Foreground-Background Integration
This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation.
Learning What to Learn for Video Object Segmentation
visionml/pytracking
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ECCV 2020
This allows us to achieve a rich internal representation of the target in the current frame, significantly increasing the segmentation accuracy of our approach.
Learning Object Depth from Camera Motion and Video Object Segmentation
Video object segmentation, i. e., the separation of a target object from background in video, has made significant progress on real and challenging videos in recent years.
RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation
The task of video object segmentation with referring expressions (language-guided VOS) is to, given a linguistic phrase and a video, generate binary masks for the object to which the phrase refers.
