Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Physarum Powered Differentiable Linear Programming Layers and Applications
Consider a learning algorithm, which involves an internal call to an optimization routine such as a generalized eigenvalue problem, a cone programming problem or even sorting. Integrating such a method as a layer(s) with…
Few-Shot LearningMeta-LearningSemantic SegmentationVideo Object Segmentation+2Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory
Video Object Segmentation (VOS) is an active research area of the visual domain. One of its fundamental sub-tasks is semi-supervised / one-shot learning: given only the segmentation mask for the first frame, the task is …
DecoderObjectOne-Shot LearningSegmentation+3Fast Template Matching and Update for Video Object Tracking and Segmentation
In this paper, the main task we aim to tackle is the multi-instance semi-supervised video object segmentation across a sequence of frames where only the first-frame box-level ground-truth is provided. Detection-based alg…
Object Trackingreinforcement-learningReinforcement LearningReinforcement Learning (RL)+6A Transductive Approach for Video Object Segmentation
Semi-supervised video object segmentation aims to separate a target object from a video sequence, given the mask in the first frame. Most of current prevailing methods utilize information from additional modules trained …
Instance SegmentationObjectOptical Flow EstimationSemantic Segmentation+3Memory Aggregation Networks for Efficient Interactive Video Object Segmentation
Interactive video object segmentation (iVOS) aims at efficiently harvesting high-quality segmentation masks of the target object in a video with user interactions. Most previous state-of-the-arts tackle the iVOS with two…
Interactive Video Object SegmentationObjectSemantic SegmentationVideo Object Segmentation+1Learning a Weakly-Supervised Video Actor-Action Segmentation Model with a Wise Selection
We address weakly-supervised video actor-action segmentation (VAAS), which extends general video object segmentation (VOS) to additionally consider action labels of the actors. The most successful methods on VOS synthesi…
Action SegmentationSegmentationSemantic SegmentationVideo Object Segmentation+1Learning What to Learn for Video Object Segmentation
Video object segmentation (VOS) is a highly challenging problem, since the target object is only defined during inference with a given first-frame reference mask. The problem of how to capture and utilize this limited ta…
Few-Shot LearningObjectOne-shot visual object segmentationSegmentation+4Collaborative Video Object Segmentation by Foreground-Background Integration
This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation. Different from previous practices that only explore the embedding learning using pixels fr…
ObjectOne-shot visual object segmentationSegmentationSemantic Segmentation+3Dual Temporal Memory Network for Efficient Video Object Segmentation
Video Object Segmentation (VOS) is typically formulated in a semi-supervised setting. Given the ground-truth segmentation mask on the first frame, the task of VOS is to track and segment the single or multiple objects of…
ObjectOne-shot visual object segmentationSegmentationSemantic Segmentation+2Learning Video Object Segmentation from Unlabeled Videos
We propose a new method for video object segmentation (VOS) that addresses object pattern learning from unlabeled videos, unlike most existing methods which rely heavily on extensive annotated data. We introduce a unifie…
ObjectRepresentation LearningSegmentationSemantic Segmentation+5Motion-Attentive Transition for Zero-Shot Video Object Segmentation
In this paper, we present a novel Motion-Attentive Transition Network (MATNet) for zero-shot video object segmentation, which provides a new way of leveraging motion information to reinforce spatio-temporal object repres…
DecoderObjectSegmentationSemantic Segmentation+4State-Aware Tracker for Real-Time Video Object Segmentation
In this work, we address the task of semi-supervised video object segmentation(VOS) and explore how to make efficient use of video property to tackle the challenge of semi-supervision. We propose a novel pipeline called …
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Learning Fast and Robust Target Models for Video Object Segmentation
Video object segmentation (VOS) is a highly challenging problem since the initial mask, defining the target object, is only given at test-time. The main difficulty is to effectively handle appearance changes and similar …
One-shot visual object segmentationSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2MAST: A Memory-Augmented Self-supervised Tracker
Recent interest in self-supervised dense tracking has yielded rapid progress, but performance still remains far from supervised methods. We propose a dense tracking model trained on videos without any annotations that su…
Semantic SegmentationSemi-Supervised Video Object SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1Directional Deep Embedding and Appearance Learning for Fast Video Object Segmentation
Most recent semi-supervised video object segmentation (VOS) methods rely on fine-tuning deep convolutional neural networks online using the given mask of the first frame or predicted masks of subsequent frames. However, …
GPUOne-shot visual object segmentationSegmentationSemantic Segmentation+3CRVOS: Clue Refining Network for Video Object Segmentation
The encoder-decoder based methods for semi-supervised video object segmentation (Semi-VOS) have received extensive attention due to their superior performances. However, most of them have complex intermediate networks wh…
DecoderObjectSegmentationSemantic Segmentation+4Fast Video Object Segmentation using the Global Context Module
We developed a real-time, high-quality semi-supervised video object segmentation algorithm. Its accuracy is on par with the most accurate, time-consuming online-learning model, while its speed is similar to the fastest t…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+3Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks
This work proposes a novel attentive graph neural network (AGNN) for zero-shot video object segmentation (ZVOS). The suggested AGNN recasts this task as a process of iterative information fusion over video graphs. Specif…
Graph Neural NetworkSegmentationSemantic SegmentationUnsupervised Video Object Segmentation+4See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
We introduce a novel network, called CO-attention Siamese Network (COSNet), to address the unsupervised video object segmentation task from a holistic view. We emphasize the importance of inherent correlation among video…
Semantic SegmentationUnsupervised Video Object SegmentationVideo Object SegmentationVideo Polyp Segmentation+1UnOVOST: Unsupervised Offline Video Object Segmentation and Tracking
We address Unsupervised Video Object Segmentation (UVOS), the task of automatically generating accurate pixel masks for salient objects in a video sequence and of tracking these objects consistently through time, without…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+3