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 201250 of 895 papers

TitleStatusHype
Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic PerspectiveCode1
AuxAdapt: Stable and Efficient Test-Time Adaptation for Temporally Consistent Video Semantic SegmentationCode1
Pixel-Level Bijective Matching for Video Object SegmentationCode1
Hierarchical Memory Matching Network for Video Object SegmentationCode1
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane DetectionCode1
Joint Inductive and Transductive Learning for Video Object SegmentationCode1
Full-Duplex Strategy for Video Object SegmentationCode1
Self-Supervised Video Object Segmentation by Motion-Aware Mask PropagationCode1
Accelerating Video Object Segmentation with Compressed VideoCode1
Domain Adaptive Video Segmentation via Temporal Consistency RegularizationCode1
A Survey on Deep Learning Technique for Video SegmentationCode1
Reciprocal Transformations for Unsupervised Video Object SegmentationCode1
Delving Deep Into Many-to-Many Attention for Few-Shot Video Object SegmentationCode1
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object SegmentationCode1
Associating Objects with Transformers for Video Object SegmentationCode1
TransVOS: Video Object Segmentation with TransformersCode1
Polygonal Point Set TrackingCode1
Attention-guided Temporally Coherent Video Object MattingCode1
Coarse to Fine Multi-Resolution Temporal Convolutional NetworkCode1
Cross-Modal Progressive Comprehension for Referring SegmentationCode1
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence LearningCode1
Guided Interactive Video Object Segmentation Using Reliability-Based Attention MapsCode1
Flow-based Video Segmentation for Human Head and ShouldersCode1
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity PerspectiveCode1
Efficient Regional Memory Network for Video Object SegmentationCode1
Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware FusionCode1
Triple-cooperative Video Shadow DetectionCode1
Temporal Memory Attention for Video Semantic SegmentationCode1
SwiftNet: Real-time Video Object SegmentationCode1
Active Boundary Loss for Semantic SegmentationCode1
Generic Event Boundary Detection: A Benchmark for Event SegmentationCode1
SSTVOS: Sparse Spatiotemporal Transformers for Video Object SegmentationCode1
Learning Motion-Appearance Co-Attention for Zero-Shot Video Object SegmentationCode1
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object SegmentationCode1
Contrastive Transformation for Self-supervised Correspondence LearningCode1
Make One-Shot Video Object Segmentation Efficient AgainCode1
TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency LossCode1
Delving into the Cyclic Mechanism in Semi-supervised Video Object SegmentationCode1
Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region RefinementCode1
Collaborative Video Object Segmentation by Multi-Scale Foreground-Background IntegrationCode1
Learning Spatio-Appearance Memory Network for High-Performance Visual TrackingCode1
Making a Case for 3D Convolutions for Object Segmentation in VideosCode1
MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object SegmentationCode1
Self-supervised Object Tracking with Cycle-consistent Siamese NetworksCode1
URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale BenchmarkCode1
Interactive Video Object Segmentation Using Global and Local Transfer ModulesCode1
Kernelized Memory Network for Video Object SegmentationCode1
Video Object Segmentation with Episodic Graph Memory NetworksCode1
Learning Object Depth from Camera Motion and Video Object SegmentationCode1
Robust Semantic Segmentation in Adverse Weather Conditions by means of Fast Video-Sequence SegmentationCode1
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Benchmark Results

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