Video Segmentation

100 papers with code • 1 benchmarks • 9 datasets

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Most implemented papers

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.

D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos

schmiddo/d2conv3d WACV 2021

We further show that D2Conv3D out-performs trivial extensions of existing dilated and deformable convolutions to 3D.

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.

Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation

simonzeng7108/video-swinunet 22 Feb 2023

This paper presents a deep learning framework for medical video segmentation.

Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation

lxtgh/tube-link ICCV 2023

Our framework is a near-online approach that takes a short subclip as input and outputs the corresponding spatial-temporal tube masks.

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.

Feature Space Optimization for Semantic Video Segmentation

infinitei/videoparsing CVPR 2016

We present an approach to long-range spatio-temporal regularization in semantic video segmentation.

STFCN: Spatio-Temporal FCN for Semantic Video Segmentation

MohsenFayyaz89/STFCN 21 Aug 2016

Current work on convolutional neural networks(CNNs) has shown that CNNs provide advanced spatial features supporting a very good performance of solutions for both image and video analysis, especially for the semantic segmentation task.

Efficient Hierarchical Graph-Based Segmentation of RGBD Videos

StevenHickson/4D_Segmentation CVPR 2014

We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based approach.