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 351–400 of 895 papers

TitleStatusHype
Geometric Algebra Planes: Convex Implicit Neural Volumes—0
Motion-Grounded Video Reasoning: Understanding and Perceiving Motion at Pixel Level—0
Zero-shot capability of SAM-family models for bone segmentation in CT scans—0
MSEG-VCUQ: Multimodal SEGmentation with Enhanced Vision Foundation Models, Convolutional Neural Networks, and Uncertainty Quantification for High-Speed Video Phase Detection DataCode0
GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting—0
Breaking The Ice: Video Segmentation for Close-Range Ice-Covered Waters—0
VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos—0
Event-guided Low-light Video Semantic Segmentation—0
Continuous Spatio-Temporal Memory Networks for 4D Cardiac Cine MRI SegmentationCode0
Addressing Issues with Working Memory in Video Object Segmentation—0
VideoSAM: A Large Vision Foundation Model for High-Speed Video SegmentationCode0
Temporal-Enhanced Multimodal Transformer for Referring Multi-Object Tracking and Segmentation—0
Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation—0
VideoSAM: Open-World Video Segmentation—0
Shift and matching queries for video semantic segmentation—0
Memory Matching is not Enough: Jointly Improving Memory Matching and Decoding for Video Object Segmentation—0
Learning Keypoints for Multi-Agent Behavior Analysis using Self-Supervision—0
LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation—0
Discriminative Spatial-Semantic VOS Solution: 1st Place Solution for 6th LSVOSCode0
CSS-Segment: 2nd Place Report of LSVOS Challenge VOS Track—0
The 2nd Solution for LSVOS Challenge RVOS Track: Spatial-temporal Refinement for Consistent Semantic Segmentation—0
The Instance-centric Transformer for the RVOS Track of LSVOS Challenge: 3rd Place Solution—0
Rethinking Video Segmentation with Masked Video Consistency: Did the Model Learn as Intended?—0
LSVOS Challenge 3rd Place Report: SAM2 and Cutie based VOS—0
Video Object Segmentation via SAM 2: The 4th Solution for LSVOS Challenge VOS Track—0
UNINEXT-Cutie: The 1st Solution for LSVOS Challenge RVOS Track—0
3D-Aware Instance Segmentation and Tracking in Egocentric Videos—0
SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation—0
Is SAM 2 Better than SAM in Medical Image Segmentation?—0
Saliency Detection in Educational Videos: Analyzing the Performance of Current Models, Identifying Limitations and Advancement Directions—0
Novel adaptation of video segmentation to 3D MRI: efficient zero-shot knee segmentation with SAM2—0
Fast Sprite Decomposition from Animated Graphics—0
Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation—0
Biomedical SAM 2: Segment Anything in Biomedical Images and VideosCode0
Strike the Balance: On-the-Fly Uncertainty based User Interactions for Long-Term Video Object SegmentationCode0
Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical videoCode0
Improving Unsupervised Video Object Segmentation via Fake Flow Generation—0
FoodMem: Near Real-time and Precise Food Video Segmentation—0
Learning Spatial-Semantic Features for Robust Video Object Segmentation—0
Rethinking Image-to-Video Adaptation: An Object-centric Perspective—0
Non-parametric Contextual Relationship Learning for Semantic Video Object Segmentation—0
Submodular video object proposal selection for semantic object segmentation—0
Context Propagation from Proposals for Semantic Video Object Segmentation—0
DaBiT: Depth and Blur informed Transformer for Joint Refocusing and Super-ResolutionCode0
Deep Unfolding-Aided Parameter Tuning for Plug-and-Play-Based Video Snapshot Compressive Imaging—0
MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation—0
Multimodal Segmentation for Vocal Tract Modeling—0
2nd Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation—0
Trusted Video Inpainting Localization via Deep Attentive Noise LearningCode0
GroPrompt: Efficient Grounded Prompting and Adaptation for Referring Video Object Segmentation—0
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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