SOTAVerified

Semi-Supervised Video Object Segmentation

The semi-supervised scenario assumes the user inputs a full mask of the object(s) of interest in the first frame of a video sequence. Methods have to produce the segmentation mask for that object(s) in the subsequent frames.

Papers

Showing 101–147 of 147 papers

TitleStatusHype
Video Object Segmentation With Dynamic Memory Networks and Adaptive Object AlignmentCode0
Robust and Efficient Memory Network for Video Object Segmentation—0
RPT: Learning Point Set Representation for Siamese Visual Tracking—0
ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: Semi-Supervised Video Object Segmentation—0
Bilateral Space Video Segmentation—0
Video Object Segmentation with Language Referring Expressions—0
Video Object Segmentation Without Temporal Information—0
Memory-Efficient Continual Learning Object Segmentation for Long Video—0
Semantically-Guided Video Object Segmentation—0
Video Propagation Networks—0
Video Segmentation via Object Flow—0
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation—0
Spatial-Temporal Multi-level Association for Video Object Segmentation—0
An Efficient 3D CNN for Action/Object Segmentation in Video—0
Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation—0
SpVOS: Efficient Video Object Segmentation with Triple Sparse Convolution—0
Look Before You Match: Instance Understanding Matters in Video Object Segmentation—0
Learning Position and Target Consistency for Memory-based Video Object Segmentation—0
Alignment Before Aggregation: Trajectory Memory Retrieval Network for Video Object Segmentation—0
Hierarchical Spatiotemporal Transformers for Video Object Segmentation—0
Global Motion Understanding in Large-Scale Video Object Segmentation—0
Fully Connected Object Proposals for Video Segmentation—0
The Second Place Solution for The 4th Large-scale Video Object Segmentation Challenge--Track 3: Referring Video Object Segmentation—0
THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation—0
Towards Good Practices for Video Object Segmentation—0
FlowVOS: Weakly-Supervised Visual Warping for Detail-Preserving and Temporally Consistent Single-Shot Video Object Segmentation—0
Flow-guided Semi-supervised Video Object Segmentation—0
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching—0
Fast video object segmentation with Spatio-Temporal GANs—0
TrickVOS: A Bag of Tricks for Video Object Segmentation—0
Fast Video Object Segmentation via Dynamic Targeting Network—0
DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation—0
VideoMatch: Matching based Video Object Segmentation—0
Pixel-Level Equalized Matching for Video Object Segmentation—0
Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks—0
PMVOS: Pixel-Level Matching-Based Video Object Segmentation—0
Collaborative Attention Memory Network for Video Object Segmentation—0
CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF—0
Online Video Object Segmentation via Convolutional Trident Network—0
Video Object Segmentation using Tracked Object Proposals—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—0
Online Adaptation of Convolutional Neural Networks for Video Object Segmentation—0
ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation—0
MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation—0
Region Aware Video Object Segmentation with Deep Motion Modeling—0
MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation—0
Memory Matching is not Enough: Jointly Improving Memory Matching and Decoding for Video Object Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2J&F90.7—Unverified
2Cutie+ (base)J&F90.5—Unverified
3ISVOS (BL30K, MS)J&F89.8—Unverified
4XMem (BL30K, MS)J&F89.5—Unverified
5ISVOS (MS)J&F88.6—Unverified
6ISVOS (BL30K)J&F88.2—Unverified
7XMem (MS)J&F88.2—Unverified
8Cutie+ (base, MEGA)J&F88.1—Unverified
9JIMDJ&F88.1—Unverified
10Cutie (base)J&F87.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinB-AOST (L'=3, MS)J&F93—Unverified
2SwinB-AOTv2-L (MS)J&F93—Unverified
3SwinB-DeAOT-LJ&F92.9—Unverified
4XMem (MS)J&F92.7—Unverified
5SwinB-AOTv2-LJ&F92.4—Unverified
6SwinB-AOST (L'=3)J&F92.4—Unverified
7R50-DeAOT-LJ&F92.3—Unverified
8R50-AOST (L'=3)J&F92.1—Unverified
9R50-AOST (L'=2)J&F92—Unverified
10DeAOT-LJ&F92—Unverified
#ModelMetricClaimedVerifiedStatus
1Cutie+ (base, MEGA)J&F88.1—Unverified
2Cutie (base, MEGA)J&F86.1—Unverified
3Cutie+ (base)J&F85.9—Unverified
4SwinB-AOST (L'=3, MS)J&F84.7—Unverified
5SwinB-AOTv2-LJ&F84.5—Unverified
6JIMD-R50J&F83.9—Unverified
7XMem (BL30K, MS)J&F83.7—Unverified
8DEVAJ&F83.2—Unverified
9XMem (MS)J&F83.1—Unverified
10SwinB-DeAOT-LJ&F82.8—Unverified