Unsupervised Video Object Segmentation On 12

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이 벤치마크에서 각 모델의 성능 결과

모델 이름	J	Paper Title	Repository
TMO (MiT-b1)	71.1	Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
WCS-Net	70.5	Unsupervised Video Object Segmentation with Joint Hotspot Tracking	-
TMO++ (RN-101)	73.1	Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
PDB	65.5	Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection	-
MATNet	69.0	Motion-Attentive Transition for Zero-Shot Video Object Segmentation
AGNN	70.8	Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks
RTNet	70.1	Reciprocal Transformations for Unsupervised Video Object Segmentation
TMO (RN-101)	71.5	Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
TMO++ (MiT-b1, MS)	73.5	Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
AMP	75.0	Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation
FakeFlow	75.1	Improving Unsupervised Video Object Segmentation via Fake Flow Generation
DPA	73.7	Dual Prototype Attention for Unsupervised Video Object Segmentation
COSNet	70.5	See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
AMC-Net	71.1	Learning Motion-Appearance Co-Attention for Zero-Shot Video Object Segmentation	-
AGS	69.7	Learning Unsupervised Video Object Segmentation Through Visual Attention	-
TMO++ (MiT-b1)	73.0	Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation

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