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 150 of 147 papers

TitleStatusHype
SAM 2: Segment Anything in Images and VideosCode11
Putting the Object Back into Video Object SegmentationCode3
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelCode3
A Distractor-Aware Memory for Visual Object Tracking with SAM2Code3
Tracking Anything with Decoupled Video SegmentationCode3
ODTrack: Online Dense Temporal Token Learning for Visual TrackingCode2
XMem++: Production-level Video Segmentation From Few Annotated FramesCode2
MixFormer: End-to-End Tracking with Iterative Mixed AttentionCode2
Fast Online Object Tracking and Segmentation: A Unifying ApproachCode2
Decoupling Features in Hierarchical Propagation for Video Object SegmentationCode2
Video Object Segmentation in Panoptic Wild ScenesCode2
Efficient Video Object Segmentation via Modulated Cross-Attention MemoryCode2
Scalable Video Object Segmentation with Identification MechanismCode2
Exploring Enhanced Contextual Information for Video-Level Object TrackingCode2
Tracking Anything in High QualityCode2
A Transductive Approach for Video Object SegmentationCode1
Associating Objects with Transformers for Video Object SegmentationCode1
Self-Supervised Video Object Segmentation by Motion-Aware Mask PropagationCode1
Learning to Learn Better for Video Object SegmentationCode1
Reliable Propagation-Correction Modulation for Video Object SegmentationCode1
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object SegmentationCode1
SSTVOS: Sparse Spatiotemporal Transformers for Video Object SegmentationCode1
Learning Video Object Segmentation from Unlabeled VideosCode1
Learning What to Learn for Video Object SegmentationCode1
Pixel-Level Bijective Matching for Video Object SegmentationCode1
Collaborative Video Object Segmentation by Multi-Scale Foreground-Background IntegrationCode1
Fast Template Matching and Update for Video Object Tracking and SegmentationCode1
Kernelized Memory Network for Video Object SegmentationCode1
Delving into the Cyclic Mechanism in Semi-supervised Video Object SegmentationCode1
Dense Unsupervised Learning for Video SegmentationCode1
Hierarchical Memory Matching Network for Video Object SegmentationCode1
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box EstimationCode1
Learning Fast and Robust Target Models for Video Object SegmentationCode1
Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment AnythingCode1
Accelerating Video Object Segmentation with Compressed VideoCode1
Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware FusionCode1
MAST: A Memory-Augmented Self-supervised TrackerCode1
Efficient Regional Memory Network for Video Object SegmentationCode1
Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic PerspectiveCode1
FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical FlowCode1
Global Spectral Filter Memory Network for Video Object SegmentationCode1
Do Different Tracking Tasks Require Different Appearance Models?Code1
LiVOS: Light Video Object Segmentation with Gated Linear MatchingCode1
Joint Inductive and Transductive Learning for Video Object SegmentationCode1
Fast Video Object Segmentation using the Global Context ModuleCode1
Per-Clip Video Object SegmentationCode1
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object SegmentationCode1
Learning Quality-aware Dynamic Memory for Video Object SegmentationCode1
Collaborative Video Object Segmentation by Foreground-Background IntegrationCode1
Directional Deep Embedding and Appearance Learning for Fast Video Object SegmentationCode1
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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
8Cutie+ (base, MEGA)J&F88.1Unverified
9JIMDJ&F88.1Unverified
10Cutie (base)J&F87.9Unverified
#ModelMetricClaimedVerifiedStatus
1SwinB-AOST (L'=3, MS)J&F93Unverified
2SwinB-AOTv2-L (MS)J&F93Unverified
3SwinB-DeAOT-LJ&F92.9Unverified
4XMem (MS)J&F92.7Unverified
5SwinB-AOTv2-LJ&F92.4Unverified
6SwinB-AOST (L'=3)J&F92.4Unverified
7R50-DeAOT-LJ&F92.3Unverified
8R50-AOST (L'=3)J&F92.1Unverified
9QDMNJ&F92Unverified
10DeAOT-LJ&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