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
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised 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
SSTVOS: Sparse Spatiotemporal Transformers for Video Object SegmentationCode1
YouTube-VOS: Sequence-to-Sequence Video Object SegmentationCode1
Make One-Shot Video Object Segmentation Efficient AgainCode1
MAST: A Memory-Augmented Self-supervised TrackerCode1
Self-Supervised Video Object Segmentation by Motion-Aware Mask PropagationCode1
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object SegmentationCode1
Reliable Propagation-Correction Modulation for Video Object SegmentationCode1
Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware FusionCode1
Recurrent Dynamic Embedding for Video Object SegmentationCode1
One-Shot Video Object SegmentationCode1
Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment AnythingCode1
Siamese Network with Interactive Transformer for Video Object SegmentationCode0
Adaptive Memory Management for Video Object SegmentationCode0
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement LearningCode0
A Generative Appearance Model for End-to-end Video Object SegmentationCode0
AGSS-VOS: Attention Guided Single-Shot Video Object SegmentationCode0
A 3D Convolutional Approach to Spectral Object Segmentation in Space and TimeCode0
Boosting Video Object Segmentation based on Scale InconsistencyCode0
BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting FramesCode0
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule RoutingCode0
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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