Video Object Segmentation - Groups

Davis dataset for video object segmentation

The Davis dataset is a benchmark for video object segmentation. It contains 30 videos with 40 frames each.

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Ref-Youtube-VOS

Ref-Youtube-VOS is an extensive referring video object segmentation dataset that comprises approximately 15,000 referring expressions associated with more than 3,900 videos.

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Associating Objects with Transformers

The Associating Objects with Transformers for video object segmentation.

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Feature Aligned Memory Network

The Feature Aligned Memory Network for video object segmentation.

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DAVIS-2016

Video object segmentation is a fundamental task in many important areas such as autonomous driving, robotic manipulation, video surveillance, and video editing.

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SegTrack-V2

Video segmentation by tracking many figure-ground segments.

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FBMS

The FBMS dataset contains 29 training videos and 30 test videos.

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DAVIS16

A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation.

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URVOS: Uniﬁed referring video object segmentation network with a large-scale ...

URVOS: Uniﬁed referring video object segmentation network with a large-scale benchmark.

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RefVOS: a closer look at referring expressions for video object segmentation

RefVOS: a closer look at referring expressions for video object segmentation.

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End-to-End Referring Video Object Segmentation with Multimodal Transformers

The referring video object segmentation task (RVOS) involves segmentation of a text-referred object instance in the frames of a given video.

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DAVIS

The DAVIS dataset is a widely used dataset for video-related tasks, consisting of approximately 2000 frames from 26 human-centric scenarios.

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A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation

A benchmark dataset and evaluation methodology for video object segmentation.

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Youtube-VIS 2019

Unsupervised video object segmentation has made significant progress in recent years, but the manual annotation of video mask datasets is expensive and limits the diversity of...

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DAVIS2017-unsupervised

Video object segmentation is a crucial task in computer vision that involves segmenting primary objects in a video sequence.

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UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via S...

Unsupervised video object segmentation has made significant progress in recent years, but the manual annotation of video mask datasets is expensive and limits the diversity of...

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Associating Objects with Transformers for Video Object Segmentation

This paper proposes a novel and efficient approach for video object segmentation by associating objects with transformers.

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YouTube-VOS 2018

The YouTube-VOS 2018 dataset is a large-scale benchmark for video object segmentation.

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Pixel-Level Bijective Matching for Video Object Segmentation

Semi-supervised video object segmentation (VOS) aims to track the designated objects present in the initial frame of a video at the pixel level.

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DAVIS-2017 TrainVal dataset

The DAVIS-2017 TrainVal dataset contains 90 video clips with diverse scenes and complex motions.

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71 datasets found