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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–500 of 895 papers

TitleStatusHype
Video Segmentation With Just a Few Strokes—0
VIDiff: Translating Videos via Multi-Modal Instructions with Diffusion Models—0
VidSeg: Training-free Video Semantic Segmentation based on Diffusion Models—0
ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation—0
Visual Representation Learning with Stochastic Frame Prediction—0
Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview—0
Visual Subtitle Feature Enhanced Video Outline Generation—0
Visual-Textual Capsule Routing for Text-Based Video Segmentation—0
VolE: A Point-cloud Framework for Food 3D Reconstruction and Volume Estimation—0
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos—0
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings—0
Weakly Supervised Multiclass Video Segmentation—0
WeClick: Weakly-Supervised Video Semantic Segmentation with Click Annotations—0
YouMVOS: An Actor-Centric Multi-Shot Video Object Segmentation Dataset—0
YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark—0
Zero-Shot 4D Lidar Panoptic Segmentation—0
Zero-shot capability of SAM-family models for bone segmentation in CT scans—0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models—0
ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: Semi-Supervised Video Object Segmentation—0
VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal—0
ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: TREK-150 Single Object Tracking—0
Sequential image processing methods for improving semantic video segmentation algorithms—0
1st Place Solution for MOSE Track in CVPR 2024 PVUW Workshop: Complex Video Object Segmentation—0
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation—0
An Analysis of Data Transformation Effects on Segment Anything 2—0
2nd Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation—0
2nd Place Solution for MOSE Track in CVPR 2024 PVUW workshop: Complex Video Object Segmentation—0
360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos—0
3D-Aware Instance Segmentation and Tracking in Egocentric Videos—0
3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition—0
3rd Place Solution for MeViS Track in CVPR 2024 PVUW workshop: Motion Expression guided Video Segmentation—0
3rd Place Solution for MOSE Track in CVPR 2024 PVUW workshop: Complex Video Object Segmentation—0
3rd Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation—0
5th Place Solution for YouTube-VOS Challenge 2022: Video Object Segmentation—0
6D Pose Estimation on Spoons and Hands—0
A Class-wise Non-salient Region Generalized Framework for Video Semantic Segmentation—0
A Coarse-To-Fine Framework For Video Object Segmentation—0
A Comprehensive Review of Modern Object Segmentation Approaches—0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects—0
Actor and Action Modular Network for Text-based Video Segmentation—0
Addressing Issues with Working Memory in Video Object Segmentation—0
A Discriminative Single-Shot Segmentation Network for Visual Object Tracking—0
Adversarial Attacks on Video Object Segmentation with Hard Region Discovery—0
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos—0
A Fast Two Pass Multi-Value Segmentation Algorithm based on Connected Component Analysis—0
Alignment Before Aggregation: Trajectory Memory Retrieval Network for Video Object Segmentation—0
A Machine Learning-based Segmentation Approach for Measuring Similarity between Sign Languages—0
An Efficient 3D CNN for Action/Object Segmentation in Video—0
An Empirical Study of Propagation-based Methods for Video Object Segmentation—0
An End-to-end 3D Convolutional Neural Network for Action Detection and Segmentation in Videos—0
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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