Unsupervised Video Object Segmentation
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RVOS: End-to-End Recurrent Network for Video Object Segmentation
Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the objects to be segmented along the sequence.
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Learning Unsupervised Video Object Segmentation Through Visual Attention
This paper conducts a systematic study on the role of visual attention in Unsupervised Video Object Segmentation (UVOS) tasks.
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See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
CVPR 2019
• carrierlxk/COSNet
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We introduce a novel network, called CO-attention Siamese Network (COSNet), to address the unsupervised video object segmentation task from a holistic view.
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Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection
ECCV 2018
• shenjianbing/PDB-ConvLSTM
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This paper proposes a fast video salient object detection model, based on a novel recurrent network architecture, named Pyramid Dilated Bidirectional ConvLSTM (PDB-ConvLSTM).
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Unsupervised Video Object Segmentation for Deep Reinforcement Learning
The detection of moving objects is done in an unsupervised way by exploiting structure from motion.
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Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
ICCV 2019
• Kinpzz/RCRNet-Pytorch
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Specifically, we present an effective video saliency detector that consists of a spatial refinement network and a spatiotemporal module.
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Tukey-Inspired Video Object Segmentation
We investigate the problem of strictly unsupervised video object segmentation, i. e., the separation of a primary object from background in video without a user-provided object mask or any training on an annotated dataset.
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Unsupervised Online Video Object Segmentation with Motion Property Understanding
Moreover, our method achieves better performance than the best unsupervised offline algorithm on the DAVIS-2016 benchmark dataset.
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