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

Showing 151200 of 895 papers

TitleStatusHype
Video Object Segmentation-aware Video Frame InterpolationCode1
Multispectral Video Semantic Segmentation: A Benchmark Dataset and BaselineCode1
Context-Aware Relative Object Queries To Unify Video Instance and Panoptic SegmentationCode1
1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object SegmentationCode1
Learning to Learn Better for Video Object SegmentationCode1
Dual Prototype Attention for Unsupervised Video Object SegmentationCode1
LVOS: A Benchmark for Long-term Video Object SegmentationCode1
Domain Adaptive Video Semantic Segmentation via Cross-Domain Moving Object MixingCode1
Global Spectral Filter Memory Network for Video Object SegmentationCode1
Self-supervised Video Representation Learning with Motion-Aware Masked AutoencodersCode1
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object RelationsCode1
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in VideoCode1
Multi-modal Segment Assemblage Network for Ad Video Editing with Importance-Coherence RewardCode1
A Simple and Powerful Global Optimization for Unsupervised Video Object SegmentationCode1
Unsupervised Video Object Segmentation via Prototype Memory NetworkCode1
Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object SegmentationCode1
SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-MaximizationCode1
Per-Clip Video Object SegmentationCode1
Multi-Attention Network for Compressed Video Referring Object SegmentationCode1
Semantic-Aware Fine-Grained CorrespondenceCode1
Mining Relations among Cross-Frame Affinities for Video Semantic SegmentationCode1
Hierarchical Feature Alignment Network for Unsupervised Video Object SegmentationCode1
Adversarial Pixel Restoration as a Pretext Task for Transferable PerturbationsCode1
Learning Quality-aware Dynamic Memory for Video Object SegmentationCode1
Tackling Background Distraction in Video Object SegmentationCode1
Domain Adaptive Video Segmentation via Temporal Pseudo SupervisionCode1
Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusCode1
Towards Robust Video Object Segmentation with Adaptive Object CalibrationCode1
Language-Bridged Spatial-Temporal Interaction for Referring Video Object SegmentationCode1
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic InformationCode1
Differentiable Soft-Masked AttentionCode1
Recurrent Dynamic Embedding for Video Object SegmentationCode1
Video K-Net: A Simple, Strong, and Unified Baseline for Video SegmentationCode1
Learning Local and Global Temporal Contexts for Video Semantic SegmentationCode1
Modeling Motion with Multi-Modal Features for Text-Based Video SegmentationCode1
In-N-Out Generative Learning for Dense Unsupervised Video SegmentationCode1
Robust Visual Tracking by SegmentationCode1
Local-Global Context Aware Transformer for Language-Guided Video SegmentationCode1
Temporal Context for Robust Maritime Obstacle DetectionCode1
RankSeg: Adaptive Pixel Classification with Image Category Ranking for SegmentationCode1
End-to-End Semi-Supervised Learning for Video Action DetectionCode1
Semi-Supervised Video Semantic Segmentation With Inter-Frame Feature ReconstructionCode1
Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross-Modal Denoising NetworksCode1
HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static ImagesCode1
Reliable Propagation-Correction Modulation for Video Object SegmentationCode1
End-to-End Referring Video Object Segmentation with Multimodal TransformersCode1
FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical FlowCode1
D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
Dense Unsupervised Learning for Video SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TMANet-50mIoU80.3Unverified
2DeltaDist-DDRNet-39mIoU79.9Unverified
3TDNet-50 [9]mIoU79.9Unverified
4PSPNet-101 [20]mIoU79.7Unverified
5PSPNet-50 [20]mIoU78.1Unverified
6LVS [12]mIoU76.8Unverified
7GRFP [15]mIoU73.6Unverified
8FCN-50 [14]mIoU70.1Unverified
9DFF [22]mIoU69.2Unverified
#ModelMetricClaimedVerifiedStatus
1TMANet-50Mean IoU76.5Unverified
2ETC-MobileNetMean IoU76.3Unverified
3TDNet-50Mean IoU76.2Unverified
4PSPNet-50Mean IoU76Unverified
5NetwarpMean IoU74.7Unverified
6GRFPMean IoU67.1Unverified
#ModelMetricClaimedVerifiedStatus
1DVIS++(VIT-L)mIoU63.8Unverified
2UniVS(Swin-L)mIoU59.8Unverified
3Tube-Link(Swin-large)mIoU59.6Unverified
4MRCFA(MiT-B5)mIoU49.9Unverified
5CFFM(MiT-B5)mIoU49.3Unverified
#ModelMetricClaimedVerifiedStatus
1WaSR-T (ResNet-101)Q60.1Unverified
2TMANet (ResNet-50)Q57.5Unverified
3CSANet (ResNet-101)Q49.1Unverified
#ModelMetricClaimedVerifiedStatus
1MVNet(DeepLabV3)mIoU54.52Unverified
2MVNet(PSPNet)mIoU54.36Unverified
3MVNet(FCN)mIoU53.9Unverified