Semi-Supervised Video Object Segmentation
95 papers with code • 15 benchmarks • 13 datasets
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.
Benchmarks
These leaderboards are used to track progress in Semi-Supervised Video Object Segmentation
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Libraries
Use these libraries to find Semi-Supervised Video Object Segmentation models and implementationsDatasets
DAVIS
DAVIS 2017
DAVIS 2016
YouTube-VOS 2018
Referring Expressions for DAVIS 2016 & 2017
VOTChallenge
MOSE
BURST
BL30K
VOT2020
Most implemented papers
Spatiotemporal CNN for Video Object Segmentation
longyin880815/STCNN
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CVPR 2019
Specifically, the temporal coherence branch pretrained in an adversarial fashion from unlabeled video data, is designed to capture the dynamic appearance and motion cues of video sequences to guide object segmentation.
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
shuangjiexu/MHP-VOS
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CVPR 2019
Extensive experiments on challenging datasets demonstrate the effectiveness of the proposed method, especially in the case of object missing.
Self-supervised Learning for Video Correspondence Flow
zlai0/CorrFlow
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Fourth, in order to shed light on the potential of self-supervised learning on the task of video correspondence flow, we probe the upper bound by training on additional data, \ie more diverse videos, further demonstrating significant improvements on video segmentation.
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.
A 3D Convolutional Approach to Spectral Object Segmentation in Space and Time
bit-ml/sfseg
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Our method is based on the power iteration for finding the principal eigenvector of a matrix, which we prove is equivalent to performing a specific set of 3D convolutions in the space-time feature volume.
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning
insomnia94/ARG
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In this paper, we aim to tackle the task of semi-supervised video object segmentation across a sequence of frames where only the ground-truth segmentation of the first frame is provided.
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.
Siam R-CNN: Visual Tracking by Re-Detection
VisualComputingInstitute/SiamR-CNN
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CVPR 2020
We present Siam R-CNN, a Siamese re-detection architecture which unleashes the full power of two-stage object detection approaches for visual object tracking.
