Video Segmentation

53 papers with code • 1 benchmarks • 6 datasets

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Most implemented papers

YouTube-VOS: Sequence-to-Sequence Video Object Segmentation

BehradToghi/ECCV_Youtube_VOS ECCV 2018

End-to-end sequential learning to explore spatial-temporal features for video segmentation is largely limited by the scale of available video segmentation datasets, i. e., even the largest video segmentation dataset only contains 90 short video clips.

One-Shot Video Object Segmentation

kmaninis/OSVOS-PyTorch 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.

Video Object Segmentation with Re-identification

lxx1991/VS-ReID 1 Aug 2017

Specifically, our Video Object Segmentation with Re-identification (VS-ReID) model includes a mask propagation module and a ReID module.

Physarum Powered Differentiable Linear Programming Layers and Applications

HeatherJiaZG/SuperGlue-pytorch 30 Apr 2020

We describe our development and show the use of our solver in a video segmentation task and meta-learning for few-shot learning.

CCNet: Criss-Cross Attention for Semantic Segmentation

speedinghzl/CCNet ICCV 2019

Compared with the non-local block, the proposed recurrent criss-cross attention module requires 11x less GPU memory usage.

Rethinking the Evaluation of Video Summaries

mayu-ot/rethinking-evs CVPR 2019

Video summarization is a technique to create a short skim of the original video while preserving the main stories/content.

TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation

verashira/TSPNet NeurIPS 2020

Sign language translation (SLT) aims to interpret sign video sequences into text-based natural language sentences.

Generic Event Boundary Detection: A Benchmark for Event Segmentation

StanLei52/GEBD ICCV 2021

This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks.

Semantic Video Segmentation : Exploring Inference Efficiency

subtri/video_inference 4 Sep 2015

We explore the efficiency of the CRF inference beyond image level semantic segmentation and perform joint inference in video frames.

A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation

fperazzi/davis CVPR 2016

The dataset, named DAVIS (Densely Annotated VIdeo Segmentation), consists of fifty high quality, Full HD video sequences, spanning multiple occurrences of common video object segmentation challenges such as occlusions, motion-blur and appearance changes.