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 301–350 of 895 papers

TitleStatusHype
Event-guided Low-light Video Semantic Segmentation—0
Click Carving: Segmenting Objects in Video with Point Clicks—0
ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation—0
An Empirical Study of Propagation-based Methods for Video Object Segmentation—0
EntitySAM: Segment Everything in Video—0
End to End Video Segmentation for Driving : Lane Detection For Autonomous Car—0
Classifier Based Graph Construction for Video Segmentation—0
An Efficient 3D CNN for Action/Object Segmentation in Video—0
An Analysis of Data Transformation Effects on Segment Anything 2—0
Leveraging Motion Information for Better Self-Supervised Video Correspondence Learning—0
EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle—0
Causal Video Object Segmentation From Persistence of Occlusions—0
Efficient Video Semantic Segmentation with Labels Propagation and Refinement—0
Efficient Video Segmentation Using Parametric Graph Partitioning—0
Learning Video Object Segmentation with Visual Memory—0
Efficient Video Segmentation Models with Per-frame Inference—0
Can Ground Truth Label Propagation from Video help Semantic Segmentation?—0
Learning to Track Any Object—0
Lifelong Learning Using a Dynamically Growing Tree of Sub-networks for Domain Generalization in Video Object Segmentation—0
LSVOS Challenge 3rd Place Report: SAM2 and Cutie based VOS—0
Efficient Unsupervised Video Object Segmentation Network Based on Motion Guidance—0
CamoSAM2: Motion-Appearance Induced Auto-Refining Prompts for Video Camouflaged Object Detection—0
A Machine Learning-based Segmentation Approach for Measuring Similarity between Sign Languages—0
Efficient Portrait Matte Creation With Layer Diffusion and Connectivity Priors—0
Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters—0
Budget-Aware Deep Semantic Video Segmentation—0
Alignment Before Aggregation: Trajectory Memory Retrieval Network for Video Object Segmentation—0
6D Pose Estimation on Spoons and Hands—0
Efficient Long-Short Temporal Attention Network for Unsupervised Video Object Segmentation—0
Efficient Heterogeneous Video Segmentation at the Edge—0
1st Place Solution for MOSE Track in CVPR 2024 PVUW Workshop: Complex Video Object Segmentation—0
Learning To Segment Dominant Object Motion From Watching Videos—0
Learning to Segment Human by Watching YouTube—0
Dynamic Video Segmentation Network—0
Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation—0
Dynamic Face Video Segmentation via Reinforcement Learning—0
A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation—0
Breaking the "Object" in Video Object Segmentation—0
5th Place Solution for YouTube-VOS Challenge 2022: Video Object Segmentation—0
Learning to Segment Moving Objects in Videos—0
Learning to Segment Referred Objects from Narrated Egocentric Videos—0
Breaking The Ice: Video Segmentation for Close-Range Ice-Covered Waters—0
Dual Temporal Memory Network for Efficient Video Object Segmentation—0
A Fast Two Pass Multi-Value Segmentation Algorithm based on Connected Component Analysis—0
Learning to Adapt to Online Streams with Distribution Shifts—0
3rd Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation—0
Harnessing Vision-Language Pretrained Models with Temporal-Aware Adaptation for Referring Video Object Segmentation—0
Learning the What and How of Annotation in Video Object Segmentation—0
Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos—0
DNN-Driven Compressive Offloading for Edge-Assisted Semantic Video Segmentation—0
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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