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 651700 of 895 papers

TitleStatusHype
Learning Video Object Segmentation from Unlabeled VideosCode1
Motion-Attentive Transition for Zero-Shot Video Object SegmentationCode1
State-Aware Tracker for Real-Time Video Object SegmentationCode1
Learning Fast and Robust Target Models for Video Object SegmentationCode1
Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration0
Efficient Semantic Video Segmentation with Per-frame InferenceCode1
MAST: A Memory-Augmented Self-supervised TrackerCode1
Directional Deep Embedding and Appearance Learning for Fast Video Object SegmentationCode1
CRVOS: Clue Refining Network for Video Object SegmentationCode0
Fast Video Object Segmentation using the Global Context ModuleCode1
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings0
Zero-Shot Video Object Segmentation via Attentive Graph Neural NetworksCode1
See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese NetworksCode1
UnOVOST: Unsupervised Offline Video Object Segmentation and TrackingCode1
Efficient Video Semantic Segmentation with Labels Propagation and Refinement0
One-Shot Weakly Supervised Video Object Segmentation0
Symmetric block-low-rank layers for fully reversible multilevel neural networks0
Automatic Video Object Segmentation via Motion-Appearance-Stream Fusion and Instance-aware Segmentation0
Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow0
D3S -- A Discriminative Single Shot Segmentation TrackerCode0
Sequential image processing methods for improving semantic video segmentation algorithms0
Learning to Track Any Object0
Anchor Diffusion for Unsupervised Video Object SegmentationCode0
Object Segmentation Tracking from Generic Video Cues0
SegEQA: Video Segmentation Based Visual Attention for Embodied Question Answering0
AGSS-VOS: Attention Guided Single-Shot Video Object SegmentationCode0
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos0
Asymmetric Cross-Guided Attention Network for Actor and Action Video Segmentation From Natural Language QueryCode0
Fast Video Object Segmentation via Dynamic Targeting Network0
Towards Good Practices for Video Object Segmentation0
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule RoutingCode0
LIP: Learning Instance Propagation for Video Object Segmentation0
RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation0
Weakly Supervised Energy-Based Learning for Action SegmentationCode0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation0
DMM-Net: Differentiable Mask-Matching Network for Video Object SegmentationCode0
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement LearningCode0
Mining Minimal Map-Segments for Visual Place Classifiers0
MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation0
Exploiting Temporality for Semi-Supervised Video SegmentationCode0
Fast Video Object Segmentation via Mask Transfer Network0
In defense of OSVOS0
RANet: Ranking Attention Network for Fast Video Object SegmentationCode0
An Empirical Study of Propagation-based Methods for Video Object Segmentation0
An Efficient 3D CNN for Action/Object Segmentation in Video0
Separable Convolutional LSTMs for Faster Video SegmentationCode1
Global Optimality Guarantees for Nonconvex Unsupervised Video Segmentation0
Spacetime Graph Optimization for Video Object Segmentation0
Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object SegmentationCode0
Dynamic Face Video Segmentation via Reinforcement Learning0
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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