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

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Showing 201–250 of 895 papers

TitleStatusHype
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking TasksCode1
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence LearningCode1
RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object SegmentationCode1
Learning Fast and Robust Target Models for Video Object SegmentationCode1
DVIS++: Improved Decoupled Framework for Universal Video SegmentationCode1
Learning Quality-aware Dynamic Memory for Video Object SegmentationCode1
M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object SegmentationCode1
Contrastive Transformation for Self-supervised Correspondence LearningCode1
ActionVOS: Actions as Prompts for Video Object SegmentationCode1
Joint Inductive and Transductive Learning for Video Object SegmentationCode1
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket SportsCode1
See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese NetworksCode1
Interactive Video Object Segmentation Using Global and Local Transfer ModulesCode1
Self-supervised Object Tracking with Cycle-consistent Siamese NetworksCode1
Efficient Multimodal Semantic Segmentation via Dual-Prompt LearningCode1
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in VideoCode1
Efficient Regional Memory Network for Video Object SegmentationCode1
Efficient Semantic Segmentation by Altering Resolutions for Compressed VideosCode1
Efficient Semantic Video Segmentation with Per-frame InferenceCode1
A Simple and Powerful Global Optimization for Unsupervised Video Object SegmentationCode1
CamSAM2: Segment Anything Accurately in Camouflaged VideosCode1
Isomer: Isomerous Transformer for Zero-shot Video Object SegmentationCode1
Kernelized Memory Network for Video Object SegmentationCode1
Accelerating Video Object Segmentation with Compressed VideoCode1
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video SegmentationCode1
CATR: Combinatorial-Dependence Audio-Queried Transformer for Audio-Visual Video SegmentationCode1
SSTVOS: Sparse Spatiotemporal Transformers for Video Object SegmentationCode1
Context-Aware Relative Object Queries To Unify Video Instance and Panoptic SegmentationCode1
End-to-End Referring Video Object Segmentation with Multimodal TransformersCode1
End-to-End Semi-Supervised Learning for Video Action DetectionCode1
End-to-End Video Matting With Trimap PropagationCode1
TarViS: A Unified Approach for Target-based Video SegmentationCode1
Temporal Aggregate Representations for Long-Range Video UnderstandingCode1
Generic Event Boundary Detection: A Benchmark for Event SegmentationCode1
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object RelationsCode1
Concatenated Masked Autoencoders as Spatial-Temporal LearnerCode1
TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in ActionCode1
In-N-Out Generative Learning for Dense Unsupervised Video SegmentationCode1
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and SegmentationCode1
Collaborative Video Object Segmentation by Multi-Scale Foreground-Background IntegrationCode1
Collaborative Video Object Segmentation by Foreground-Background IntegrationCode1
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object SegmentationCode1
Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic PerspectiveCode1
Global Knowledge Calibration for Fast Open-Vocabulary SegmentationCode1
TransVOS: Video Object Segmentation with TransformersCode1
1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object SegmentationCode1
FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical FlowCode1
High Temporal Consistency through Semantic Similarity Propagation in Semi-Supervised Video Semantic Segmentation for Autonomous FlightCode1
HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static ImagesCode1
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All datasetsCityscapes valCamVidVSPWLaRSMultispectral Video Semantic Segmentation

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TMANet-50mIoU80.3—Unverified
2TDNet-50 [9]mIoU79.9—Unverified
3DeltaDist-DDRNet-39mIoU79.9—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