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 126147 of 147 papers

TitleStatusHype
FlowVOS: Weakly-Supervised Visual Warping for Detail-Preserving and Temporally Consistent Single-Shot Video Object Segmentation0
Flow-guided Semi-supervised Video Object Segmentation0
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching0
Fast video object segmentation with Spatio-Temporal GANs0
TrickVOS: A Bag of Tricks for Video Object Segmentation0
Fast Video Object Segmentation via Dynamic Targeting Network0
DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation0
VideoMatch: Matching based Video Object Segmentation0
Pixel-Level Equalized Matching for Video Object Segmentation0
Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks0
PMVOS: Pixel-Level Matching-Based Video Object Segmentation0
Collaborative Attention Memory Network for Video Object Segmentation0
CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF0
Online Video Object Segmentation via Convolutional Trident Network0
Video Object Segmentation using Tracked Object Proposals0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning0
Online Adaptation of Convolutional Neural Networks for Video Object Segmentation0
ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation0
MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation0
Region Aware Video Object Segmentation with Deep Motion Modeling0
MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation0
Memory Matching is not Enough: Jointly Improving Memory Matching and Decoding for Video Object Segmentation0
Show:102550
← PrevPage 6 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