SOTAVerified

Video Semantic Segmentation

The goal of video semantic segmentation is to assign a predefined class to each pixel in all frames of a video. This requires the model not only to predict accurate segmentation masks but also to ensure that these masks remain temporally consistent across frames. This task has broad applications in areas such as autonomous driving, medical video analysis, and AR/VR.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 895 papers

TitleStatusHype
Learning to Segment Moving Objects in Videos—0
Learning to Segment Human by Watching YouTube—0
BoLTVOS: Box-Level Tracking for Video Object Segmentation—0
Learning to Adapt to Online Streams with Distribution Shifts—0
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation—0
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos—0
Learning Referring Video Object Segmentation from Weak Annotation—0
Sequential image processing methods for improving semantic video segmentation algorithms—0
MEDIAPI-SKEL - A 2D-Skeleton Video Database of French Sign Language With Aligned French Subtitles—0
MED-VT++: Unifying Multimodal Learning with a Multiscale Encoder-Decoder Video Transformer—0
Memory-Efficient Continual Learning Object Segmentation for Long Video—0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation—0
Motion Prediction in Visual Object Tracking—0
Learning Position and Target Consistency for Memory-based Video Object Segmentation—0
Discriminative Online Learning for Fast Video Object Segmentation—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—0
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs—0
Learning Keypoints for Multi-Agent Behavior Analysis using Self-Supervision—0
Bilateral Space Video Segmentation—0
Adversarial Attacks on Video Object Segmentation with Hard Region Discovery—0
Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation—0
Beyond Semantic Image Segmentation : Exploring Efficient Inference in Video—0
Learning a Weakly-Supervised Video Actor-Action Segmentation Model with a Wise Selection—0
DeVOS: Flow-Guided Deformable Transformer for Video Object Segmentation—0
A Discriminative Single-Shot Segmentation Network for Visual Object Tracking—0
Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time—0
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
Immersive Human-Machine Teleoperation Framework for Precision Agriculture: Integrating UAV-based Digital Mapping and Virtual Reality Control—0
DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation—0
Learning Pixel Trajectories with Multiscale Contrastive Random Walks—0
MaskRNN: Instance Level Video Object Segmentation—0
Key Instance Selection for Unsupervised Video Object Segmentation—0
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation—0
Learning Representations from Audio-Visual Spatial Alignment—0
Learning Spatial-Semantic Features for Robust Video Object Segmentation—0
Learning the What and How of Annotation in Video Object Segmentation—0
JOTS: Joint Online Tracking and Segmentation—0
Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos—0
Joint Tracking and Segmentation of Multiple Targets—0
Learning To Segment Dominant Object Motion From Watching Videos—0
Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation—0
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation—0
Iteratively Selecting an Easy Reference Frame Makes Unsupervised Video Object Segmentation Easier—0
Learning to Sort Image Sequences via Accumulated Temporal Differences—0
Is Two-shot All You Need? A Label-efficient Approach for Video Segmentation in Breast Ultrasound—0
Is Segment Anything Model 2 All You Need for Surgery Video Segmentation? A Systematic Evaluation—0
Is SAM 2 Better than SAM in Medical Image Segmentation?—0
AUTV: Creating Underwater Video Datasets with Pixel-wise Annotations—0
ISEC: Iterative over-Segmentation via Edge Clustering—0
Deep Unfolding-Aided Parameter Tuning for Plug-and-Play-Based Video Snapshot Compressive Imaging—0
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All datasetsCityscapes valCamVidVSPWLaRSMultispectral Video Semantic Segmentation

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TMANet-50mIoU80.3—Unverified
2DeltaDist-DDRNet-39mIoU79.9—Unverified
3TDNet-50 [9]mIoU79.9—Unverified
4PSPNet-101 [20]mIoU79.7—Unverified
5PSPNet-50 [20]mIoU78.1—Unverified
6LVS [12]mIoU76.8—Unverified
7GRFP [15]mIoU73.6—Unverified
8FCN-50 [14]mIoU70.1—Unverified
9DFF [22]mIoU69.2—Unverified
#ModelMetricClaimedVerifiedStatus
1TMANet-50Mean IoU76.5—Unverified
2ETC-MobileNetMean IoU76.3—Unverified
3TDNet-50Mean IoU76.2—Unverified
4PSPNet-50Mean IoU76—Unverified
5NetwarpMean IoU74.7—Unverified
6GRFPMean IoU67.1—Unverified
#ModelMetricClaimedVerifiedStatus
1DVIS++(VIT-L)mIoU63.8—Unverified
2UniVS(Swin-L)mIoU59.8—Unverified
3Tube-Link(Swin-large)mIoU59.6—Unverified
4MRCFA(MiT-B5)mIoU49.9—Unverified
5CFFM(MiT-B5)mIoU49.3—Unverified
#ModelMetricClaimedVerifiedStatus
1WaSR-T (ResNet-101)Q60.1—Unverified
2TMANet (ResNet-50)Q57.5—Unverified
3CSANet (ResNet-101)Q49.1—Unverified
#ModelMetricClaimedVerifiedStatus
1MVNet(DeepLabV3)mIoU54.52—Unverified
2MVNet(PSPNet)mIoU54.36—Unverified
3MVNet(FCN)mIoU53.9—Unverified