One-shot visual object segmentation
26 papers with code • 2 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in One-shot visual object segmentation
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YouTube-VOS 2018
Most implemented papers
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.
Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
sydney0zq/PTSNet
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Video object segmentation (VOS) aims at pixel-level object tracking given only the annotations in the first frame.
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
In practice, it performs similarly to the Hungarian algorithm during inference.
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
KevinDuarte/CapsuleVOS
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ICCV 2019
In this work we propose a capsule-based approach for semi-supervised video object segmentation.
AGSS-VOS: Attention Guided Single-Shot Video Object Segmentation
Jia-Research-Lab/AGSS-VOS
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ICCV 2019
In this paper, we propose AGSS-VOS to segment multiple objects in one feed-forward path via instance-agnostic and instance-specific modules.
Directional Deep Embedding and Appearance Learning for Fast Video Object Segmentation
YingjieYin/Directional-Deep-Embedding-and-Appearance-Learning-for-Fast-Video-Object-Segmentation
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We propose a directional deep embedding and appearance learning (DDEAL) method, which is free of the online fine-tuning process, for fast VOS.
ALBA : Reinforcement Learning for Video Object Segmentation
kini5gowda/ALBA-RL-for-VOS
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We treat this as a grouping problem by exploiting object proposals and making a joint inference about grouping over both space and time.
Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching
In this work, we study an RNN-based architecture and address some of these issues by proposing a hybrid sequence-to-sequence architecture named HS2S, utilizing a dual mask propagation strategy that allows incorporating the information obtained from correspondence matching.
Collaborative Video Object Segmentation by Multi-Scale Foreground-Background Integration
z-x-yang/CFBI
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This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation.
Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation
lyxok1/STM-Training
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NeurIPS 2020
In this paper, we address several inadequacies of current video object segmentation pipelines.
