Video Segmentation
105 papers with code • 1 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Video Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Datasets
BDD100K
SegTrack-v2
Dynamic Replica
PP-HumanSeg14K
PETRAW
EgoProceL
TikTok Dataset
ConferenceVideoSegmentationDataset
Infinity Spills Basic Dataset
Subtasks
Latest papers
Hierarchical Graph Pattern Understanding for Zero-Shot VOS
nust-machine-intelligence-laboratory/hgpu
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However, existing optical flow-based methods have a significant dependency on optical flow, which results in poor performance when the optical flow estimation fails for a particular scene.
MaXTron: Mask Transformer with Trajectory Attention for Video Panoptic Segmentation
tacju/maxtron
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To alleviate the issue, we propose to adapt the trajectory attention for both the dense pixel features and object queries, aiming to improve the short-term and long-term tracking results, respectively.
Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object Segmentation
In this paper, we propose a simple yet effective approach for self-supervised video object segmentation (VOS).
Concatenated Masked Autoencoders as Spatial-Temporal Learner
minhoooo1/catmae
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Learning representations from videos requires understanding continuous motion and visual correspondences between frames.
SimLVSeg: Simplifying Left Ventricular Segmentation in 2D+Time Echocardiograms with Self- and Weakly-Supervised Learning
From calculating biomarkers such as ejection fraction to the probability of a patient's heart failure, accurate segmentation of the heart structures allows doctors to assess the heart's condition and devise treatments with greater precision and accuracy.
MediViSTA-SAM: Zero-shot Medical Video Analysis with Spatio-temporal SAM Adaptation for Echocardiography
The Segmentation Anything Model (SAM) has gained significant attention for its robust generalization capabilities across diverse downstream tasks.
Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation
Furthermore, we propose a multi-view fusion layer based temporal module which is equipped with a set of object slots and interacts with features from different views by attention mechanism to fulfill sufficient object representation completion.
PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation
Our dataset poses new challenges in panoramic VOS and we hope that our PanoVOS can advance the development of panoramic segmentation/tracking.
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
xmed-lab/GraphEcho
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ICCV 2023
This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentation, where the goal is to generalize the model trained on the source domain to other unlabelled target domains.
GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation
Additionally, a Multi-view Local-based Fusion Module (MLFM) is designed to extract correlations of cardiac structures from different views.
