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 5175 of 147 papers

TitleStatusHype
Learning Video Object Segmentation from Unlabeled VideosCode1
SSTVOS: Sparse Spatiotemporal Transformers for Video Object SegmentationCode1
Learning What to Learn for Video Object SegmentationCode1
Lester: rotoscope animation through video object segmentation and trackingCode1
LiVOS: Light Video Object Segmentation with Gated Linear MatchingCode1
Video Object Segmentation using Space-Time Memory NetworksCode1
Self-Supervised Video Object Segmentation by Motion-Aware Mask PropagationCode1
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object SegmentationCode1
Make One-Shot Video Object Segmentation Efficient AgainCode1
MAST: A Memory-Augmented Self-supervised TrackerCode1
UnOVOST: Unsupervised Offline Video Object Segmentation and TrackingCode1
TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency LossCode1
Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware FusionCode1
One-Shot Video Object SegmentationCode1
Video Object Segmentation with Dynamic Query ModulationCode1
Collaborative Video Object Segmentation by Foreground-Background IntegrationCode1
ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: Semi-Supervised Video Object Segmentation0
Alignment Before Aggregation: Trajectory Memory Retrieval Network for Video Object Segmentation0
An Efficient 3D CNN for Action/Object Segmentation in Video0
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation0
Bilateral Space Video Segmentation0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning0
CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF0
Collaborative Attention Memory Network for Video Object Segmentation0
DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation0
Show:102550
← PrevPage 3 of 6Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAM2J&F90.7Unverified
2Cutie+ (base)J&F90.5Unverified
3ISVOS (BL30K, MS)J&F89.8Unverified
4XMem (BL30K, MS)J&F89.5Unverified
5ISVOS (MS)J&F88.6Unverified
6ISVOS (BL30K)J&F88.2Unverified
7XMem (MS)J&F88.2Unverified
8JIMDJ&F88.1Unverified
9Cutie+ (base, MEGA)J&F88.1Unverified
10Cutie (base)J&F87.9Unverified
#ModelMetricClaimedVerifiedStatus
1SwinB-AOTv2-L (MS)J&F93Unverified
2SwinB-AOST (L'=3, MS)J&F93Unverified
3SwinB-DeAOT-LJ&F92.9Unverified
4XMem (MS)J&F92.7Unverified
5SwinB-AOST (L'=3)J&F92.4Unverified
6SwinB-AOTv2-LJ&F92.4Unverified
7R50-DeAOT-LJ&F92.3Unverified
8R50-AOST (L'=3)J&F92.1Unverified
9SwinB-AOT-LJ&F92Unverified
10XMem (BL30K)J&F92Unverified
#ModelMetricClaimedVerifiedStatus
1Cutie+ (base, MEGA)J&F88.1Unverified
2Cutie (base, MEGA)J&F86.1Unverified
3Cutie+ (base)J&F85.9Unverified
4SwinB-AOST (L'=3, MS)J&F84.7Unverified
5SwinB-AOTv2-LJ&F84.5Unverified
6JIMD-R50J&F83.9Unverified
7XMem (BL30K, MS)J&F83.7Unverified
8DEVAJ&F83.2Unverified
9XMem (MS)J&F83.1Unverified
10SwinB-DeAOT-LJ&F82.8Unverified