15 datasets found

The dataset used for video object segmentation task, where a first frame labelled with the foreground object mask, the goal is to find the corresponding object pixels in future...

The dataset used for video object segmentation task, where a first frame labelled with the masks of several object instances, one aims to find the corresponding masks of objects...

The dataset used for video object segmentation task, where a first frame labelled with the masks of several object instances, one aims to find the corresponding masks of objects...

A benchmark dataset and evaluation methodology for video object segmentation.

The DAVIS 2017 challenge dataset is a benchmark for video object segmentation. It consists of 150 sequences with multiple objects and instance-level pixel-wise annotations.

A benchmark dataset and evaluation methodology for video object segmentation.

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

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

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

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

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

A benchmark dataset and evaluation methodology for video object segmentation.

YouTube-VOS 2018 and 2019 datasets are benchmarks for video object segmentation, featuring various challenging scenarios.

DAVIS 2016 and 2017 datasets are benchmarks for video object segmentation, featuring various challenging scenarios.

MOSE 2023 dataset is a novel VOS benchmark featuring extreme scenarios of the video sequence which are not handled good enough by existing VOS methods.