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
D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in VideosCode1
MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object SegmentationCode1
FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical FlowCode1
Actor and Action Video Segmentation from a SentenceCode1
MAST: A Memory-Augmented Self-supervised TrackerCode1
A Simple Video Segmenter by Tracking Objects Along Axial TrajectoriesCode1
Mining Relations among Cross-Frame Affinities for Video Semantic SegmentationCode1
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object SegmentationCode1
Cross-Modal Progressive Comprehension for Referring SegmentationCode1
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object SegmentationCode1
DC-SAM: In-Context Segment Anything in Images and Videos via Dual ConsistencyCode1
Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationCode1
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and GrounderCode1
CrOC: Cross-View Online Clustering for Dense Visual Representation LearningCode1
A Survey on Deep Learning Technique for Video SegmentationCode1
Exploiting Temporal State Space Sharing for Video Semantic SegmentationCode1
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object RelationsCode1
Deep Feature Flow for Video RecognitionCode1
Few-shot Structure-Informed Machinery Part Segmentation with Foundation Models and Graph Neural NetworksCode1
Associating Objects with Transformers for Video Object SegmentationCode1
Multi-modal Segment Assemblage Network for Ad Video Editing with Importance-Coherence RewardCode1
Full-Duplex Strategy for Video Object SegmentationCode1
General and Task-Oriented Video SegmentationCode1
Event-assisted Low-Light Video Object SegmentationCode1
Active Boundary Loss for Semantic SegmentationCode1
Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic PerspectiveCode1
Delving Deep Into Many-to-Many Attention for Few-Shot Video Object SegmentationCode1
Fast Template Matching and Update for Video Object Tracking and SegmentationCode1
Dense Unsupervised Learning for Video SegmentationCode1
Depth-aware Test-Time Training for Zero-shot Video Object SegmentationCode1
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic InformationCode1
Mask Propagation for Efficient Video Semantic SegmentationCode1
Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object SegmentationCode1
3rd Place Solution for PVUW2023 VSS Track: A Large Model for Semantic Segmentation on VSPWCode1
Differentiable Soft-Masked AttentionCode1
Directional Deep Embedding and Appearance Learning for Fast Video Object SegmentationCode1
Hierarchical Memory Matching Network for Video Object SegmentationCode1
Contrastive Transformation for Self-supervised Correspondence LearningCode1
Learning Spatio-Appearance Memory Network for High-Performance Visual TrackingCode1
ActionVOS: Actions as Prompts for Video Object SegmentationCode1
M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object SegmentationCode1
Accelerating Video Object Segmentation with Compressed VideoCode1
Local-Global Context Aware Transformer for Language-Guided Video SegmentationCode1
Boosting Video Object Segmentation via Space-time Correspondence LearningCode1
Domain Adaptive Video Segmentation via Temporal Consistency RegularizationCode1
Domain Adaptive Video Segmentation via Temporal Pseudo SupervisionCode1
Domain Adaptive Video Semantic Segmentation via Cross-Domain Moving Object MixingCode1
A Simple and Powerful Global Optimization for Unsupervised Video Object SegmentationCode1
End-to-End Referring Video Object Segmentation with Multimodal TransformersCode1
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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