Semi Supervised Video Object Segmentation On 20

评估指标

D16 val (F)
D16 val (G)
D16 val (J)
D17 test (F)
D17 test (G)
D17 test (J)
D17 val (F)
D17 val (G)
D17 val (J)
FPS

评测结果

各个模型在此基准测试上的表现结果

Paper TitleRepository
HMMN90.689.488.2---83.180.477.710.0Hierarchical Memory Matching Network for Video Object Segmentation
TBD86.286.887.572.269.466.682.380.077.650.1Tackling Background Distraction in Video Object Segmentation
AOT-S------82.079.276.440.0Associating Objects with Transformers for Video Object Segmentation
SSTVOS------81.478.475.4-SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation
JOINT------81.278.676.04.00Joint Inductive and Transductive Learning for Video Object Segmentation
SWEM89.088.187.3---79.877.274.536.0SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
STG-Net86.085.785.466.563.159.777.974.771.5-Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation-
KMN88.187.687.1---77.876.074.28.33Kernelized Memory Network for Video Object Segmentation
CFBI86.986.185.3---77.774.972.15.56Collaborative Video Object Segmentation by Foreground-Background Integration
LCM------77.275.273.18.47Learning Position and Target Consistency for Memory-based Video Object Segmentation-
RMNet82.381.580.6---77.275.072.811.9Efficient Regional Memory Network for Video Object Segmentation
LWL------76.374.372.214.0Learning What to Learn for Video Object Segmentation
AFB-URR------76.174.673.04.00Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
TVOS---67.463.158.874.772.369.937.0A Transductive Approach for Video Object Segmentation
BMVOS81.482.282.964.762.760.774.772.770.745.9Pixel-Level Bijective Matching for Video Object Segmentation
STM88.186.584.8---74.071.669.26.25Video Object Segmentation using Space-Time Memory Networks
GC85.786.687.6---73.571.469.325.0Fast Video Object Segmentation using the Global Context Module
DMM-Net------73.370.768.1-DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
FEELVOS83.181.780.357.554.451.272.369.165.92.22FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation
DIPNet86.486.185.8-55.2-71.668.565.30.92--
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Semi Supervised Video Object Segmentation On 20 | SOTA | HyperAI超神经