Video Instance Segmentation

60 papers with code • 8 benchmarks • 8 datasets

The goal of video instance segmentation is simultaneous detection, segmentation and tracking of instances in videos. In words, it is the first time that the image instance segmentation problem is extended to the video domain.

To facilitate research on this new task, a large-scale benchmark called YouTube-VIS, which consists of 2,883 high-resolution YouTube videos, a 40-category label set and 131k high-quality instance masks is built.


Use these libraries to find Video Instance Segmentation models and implementations
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Most implemented papers

Simple Online and Realtime Tracking with a Deep Association Metric

nwojke/deep_sort 21 Mar 2017

Simple Online and Realtime Tracking (SORT) is a pragmatic approach to multiple object tracking with a focus on simple, effective algorithms.

Video Instance Segmentation

Epiphqny/VisTR ICCV 2019

The goal of this new task is simultaneous detection, segmentation and tracking of instances in videos.

Instances as Queries

hustvl/QueryInst ICCV 2021

The key insight of QueryInst is to leverage the intrinsic one-to-one correspondence in object queries across different stages, as well as one-to-one correspondence between mask RoI features and object queries in the same stage.

Mask2Former for Video Instance Segmentation

facebookresearch/Mask2Former 20 Dec 2021

We find Mask2Former also achieves state-of-the-art performance on video instance segmentation without modifying the architecture, the loss or even the training pipeline.

End-to-End Video Instance Segmentation with Transformers

Epiphqny/VisTR CVPR 2021

Here, we propose a new video instance segmentation framework built upon Transformers, termed VisTR, which views the VIS task as a direct end-to-end parallel sequence decoding/prediction problem.

Temporally Efficient Vision Transformer for Video Instance Segmentation

hustvl/tevit CVPR 2022

To effectively and efficiently model the crucial temporal information within a video clip, we propose a Temporally Efficient Vision Transformer (TeViT) for video instance segmentation (VIS).

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations

wvangansbeke/Revisiting-Contrastive-SSL NeurIPS 2021

Contrastive self-supervised learning has outperformed supervised pretraining on many downstream tasks like segmentation and object detection.

UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution

dulucas/uvo_challenge 22 Oct 2021

In this report, we introduce our (pretty straightforard) two-step "detect-then-match" video instance segmentation method.

SeqFormer: Sequential Transformer for Video Instance Segmentation

wjf5203/SeqFormer 15 Dec 2021

Nevertheless, we observe that a stand-alone instance query suffices for capturing a time sequence of instances in a video, but attention mechanisms shall be done with each frame independently.

RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation

openseg-group/rankseg 8 Mar 2022

Given an input image or video, our framework first conducts multi-label classification over the complete label, then sorts the complete label and selects a small subset according to their class confidence scores.