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 251–300 of 895 papers

TitleStatusHype
DeepPyramid+: Medical Image Segmentation using Pyramid View Fusion and Deformable Pyramid Reception—0
Efficient Multimodal Semantic Segmentation via Dual-Prompt LearningCode1
VIDiff: Translating Videos via Multi-Modal Instructions with Diffusion Models—0
SimulFlow: Simultaneously Extracting Feature and Identifying Target for Unsupervised Video Object Segmentation—0
A Simple Video Segmenter by Tracking Objects Along Axial TrajectoriesCode1
Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object SegmentationCode1
SEGIC: Unleashing the Emergent Correspondence for In-Context SegmentationCode1
Unified Domain Adaptive Semantic SegmentationCode1
DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance FieldsCode0
Correlation-aware active learning for surgery video segmentation—0
Sketch-based Video Object Segmentation: Benchmark and Analysis—0
Learning the What and How of Annotation in Video Object Segmentation—0
ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification—0
Concatenated Masked Autoencoders as Spatial-Temporal LearnerCode1
Mask Propagation for Efficient Video Semantic SegmentationCode1
SpVOS: Efficient Video Object Segmentation with Triple Sparse Convolution—0
Putting the Object Back into Video Object SegmentationCode3
Understanding Video Transformers for Segmentation: A Survey of Application and Interpretability—0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models—0
Sub-token ViT Embedding via Stochastic Resonance TransformersCode0
CoralVOS: Dataset and Benchmark for Coral Video Segmentation—0
SimLVSeg: Simplifying Left Ventricular Segmentation in 2D+Time Echocardiograms with Self- and Weakly-Supervised LearningCode0
Memory-Efficient Continual Learning Object Segmentation for Long Video—0
Treating Motion as Option with Output Selection for Unsupervised Video Object SegmentationCode1
Adversarial Attacks on Video Object Segmentation with Hard Region Discovery—0
MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for EchocardiographyCode1
Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric RepresentationCode0
SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset—0
Efficient Long-Short Temporal Attention Network for Unsupervised Video Object Segmentation—0
PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video SegmentationCode1
Fully Transformer-Equipped Architecture for End-to-End Referring Video Object Segmentation—0
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic SegmentationCode0
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video SegmentationCode1
Multi-grained Temporal Prototype Learning for Few-shot Video Object SegmentationCode0
GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video SegmentationCode0
CATR: Combinatorial-Dependence Audio-Queried Transformer for Audio-Visual Video SegmentationCode1
Temporal-aware Hierarchical Mask Classification for Video Semantic SegmentationCode0
Temporal Collection and Distribution for Referring Video Object Segmentation—0
Tracking Anything with Decoupled Video SegmentationCode3
Robust Visual Tracking by Motion Analyzing—0
Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited SamplesCode0
VideoCutLER: Surprisingly Simple Unsupervised Video Instance SegmentationCode3
Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation—0
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and SegmentationCode1
Robotic Scene Segmentation with Memory Network for Runtime Surgical Context InferenceCode0
LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-trainingCode0
MEGA: Multimodal Alignment Aggregation and Distillation For Cinematic Video Segmentation—0
Scalable Video Object Segmentation with Simplified Framework—0
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and BenchmarkCode1
MeViS: A Large-scale Benchmark for Video Segmentation with Motion ExpressionsCode2
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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