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 551–600 of 895 papers

TitleStatusHype
Visual Subtitle Feature Enhanced Video Outline Generation—0
Two-Stream Networks for Object Segmentation in Videos—0
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation—0
Region Aware Video Object Segmentation with Deep Motion Modeling—0
Personalized PCA: Decoupling Shared and Unique FeaturesCode0
MAC-DO: An Efficient Output-Stationary GEMM Accelerator for CNNs Using DRAM Technology—0
The Second Place Solution for The 4th Large-scale Video Object Segmentation Challenge--Track 3: Referring Video Object Segmentation—0
5th Place Solution for YouTube-VOS Challenge 2022: Video Object Segmentation—0
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation—0
An Image Processing Pipeline for Camera Trap Time-Lapse RecordingsCode0
A Machine Learning-based Segmentation Approach for Measuring Similarity between Sign Languages—0
TubeFormer-DeepLab: Video Mask Transformer—0
Collaborative Attention Memory Network for Video Object Segmentation—0
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion—0
Boosting Video Object Segmentation based on Scale InconsistencyCode0
Representation Recycling for Streaming Video AnalysisCode0
Self-Supervised Video Object Segmentation via Cutout Prediction and Tagging—0
Adaptive Memory Management for Video Object SegmentationCode0
3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition—0
Implicit Motion-Compensated Network for Unsupervised Video Object SegmentationCode0
Human Instance Segmentation and Tracking via Data Association and Single-stage Detector—0
Deeply Interleaved Two-Stream Encoder for Referring Video Segmentation—0
DNN-Driven Compressive Offloading for Edge-Assisted Semantic Video Segmentation—0
Temporal Transductive Inference for Few-Shot Video Object SegmentationCode0
Delta Distillation for Efficient Video ProcessingCode0
Object discovery and representation networksCode0
Revisiting Click-based Interactive Video Object SegmentationCode0
Efficient Video Segmentation Models with Per-frame Inference—0
Box Supervised Video Segmentation Proposal NetworkCode0
Borrowing from yourself: Faster future video segmentation with partial channel updateCode0
Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks—0
Learning Pixel Trajectories with Multiscale Contrastive Random Walks—0
YouMVOS: An Actor-Centric Multi-Shot Video Object Segmentation Dataset—0
Multi-Level Representation Learning With Semantic Alignment for Referring Video Object Segmentation—0
Real-Time, Accurate, and Consistent Video Semantic Segmentation via Unsupervised Adaptation and Cross-Unit Deployment on Mobile Device—0
Siamese Network with Interactive Transformer for Video Object SegmentationCode0
Temporally Constrained Neural Networks (TCNN): A framework for semi-supervised video semantic segmentation—0
Iteratively Selecting an Easy Reference Frame Makes Unsupervised Video Object Segmentation Easier—0
A Discriminative Single-Shot Segmentation Network for Visual Object Tracking—0
MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation—0
Learning To Segment Dominant Object Motion From Watching Videos—0
Hierarchical interaction network for video object segmentation from referring expressions—0
FlowVOS: Weakly-Supervised Visual Warping for Detail-Preserving and Temporally Consistent Single-Shot Video Object Segmentation—0
Video Salient Object Detection via Contrastive Features and Attention Modules—0
SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation—0
Perceptual Consistency in Video Segmentation—0
Multi-Object Tracking and Segmentation with a Space-Time Memory Network—0
Temporally stable video segmentation without video annotations—0
ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation—0
Space Time Recurrent Memory Network—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