Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Making a Case for 3D Convolutions for Object Segmentation in Videos
The task of object segmentation in videos is usually accomplished by processing appearance and motion information separately using standard 2D convolutional networks, followed by a learned fusion of the two sources of in…
DecoderSegmentationSemantic SegmentationUnsupervised Video Object Segmentation+5ScribbleBox: Interactive Annotation Framework for Video Object Segmentation
Manually labeling video datasets for segmentation tasks is extremely time consuming. In this paper, we introduce ScribbleBox, a novel interactive framework for annotating object instances with masks in videos. In particu…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation
In this paper, we present a novel end-to-end learning neural network, i.e., MATNet, for zero-shot video object segmentation (ZVOS). Motivated by the human visual attention behavior, MATNet leverages motion cues as a bott…
ObjectSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+3DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping
We describe an unsupervised method to detect and segment portions of images of live scenes that, at some point in time, are seen moving as a coherent whole, which we refer to as objects. Our method first partitions the m…
Continual LearningObjectobject-detectionObject Detection+7Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-task Baseline
Moving object segmentation is a crucial task for autonomous vehicles as it can be used to segment objects in a class agnostic manner based on their motion cues. It enables the detection of unseen objects during training …
Autonomous DrivingAutonomous VehiclesGPUInstance Segmentation+9Curriculum Learning for Recurrent Video Object Segmentation
Video object segmentation can be understood as a sequence-to-sequence task that can benefit from the curriculum learning strategies for better and faster training of deep neural networks. This work explores different sch…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationLearning Discriminative Feature with CRF for Unsupervised Video Object Segmentation
In this paper, we introduce a novel network, called discriminative feature network (DFNet), to address the unsupervised video object segmentation task. To capture the inherent correlation among video frames, we learn dis…
RGB Salient Object DetectionSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1Self-supervised Object Tracking with Cycle-consistent Siamese Networks
Self-supervised learning for visual object tracking possesses valuable advantages compared to supervised learning, such as the non-necessity of laborious human annotations and online training. In this work, we exploit an…
ObjectObject TrackingRegion ProposalSelf-Supervised Learning+4Unsupervised Video Object Segmentation with Joint Hotspot Tracking
Object tracking is a well-studied problem in computer vision while identifying salient spots of objects in a video is a less explored direction in the literature. Video eye gaze estimation methods aim to tackle a related…
Gaze EstimationObjectObject TrackingSegmentation+4Memory Selection Network for Video Propagation
Video propagation is a fundamental problem in video processing where guidance frame predictions are propagated to guide predictions of the target frame. Previous research mainly treats the previous adjacent frame as guid…
ColorizationSemantic SegmentationVideo Object SegmentationVideo Propagation+1URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark
We propose a unified referring video object segmentation network (URVOS). URVOS takes a video and a referring expression as inputs, and estimates the {object masks} referred by the given language expression in the whole …
ObjectOne-shot visual object segmentationReferring ExpressionReferring Expression Segmentation+5Kernelized Memory Network for Video Object Segmentation
Semi-supervised video object segmentation (VOS) is a task that involves predicting a target object in a video when the ground truth segmentation mask of the target object is given in the first frame. Recently, space-time…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Interactive Video Object Segmentation Using Global and Local Transfer Modules
An interactive video object segmentation algorithm, which takes scribble annotations on query objects as input, is proposed in this paper. We develop a deep neural network, which consists of the annotation network (A-Net…
DecoderInteractive Video Object SegmentationSegmentationSemantic Segmentation+2Video Object Segmentation with Episodic Graph Memory Networks
How to make a segmentation model efficiently adapt to a specific video and to online target appearance variations are fundamentally crucial issues in the field of video object segmentation. In this work, a graph memory n…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching
Significant progress has been made in Video Object Segmentation (VOS), the video object tracking task in its finest level. While the VOS task can be naturally decoupled into image semantic segmentation and video object t…
ObjectObject TrackingOne-Shot LearningSegmentation+6Learning Object Depth from Camera Motion and Video Object Segmentation
Video object segmentation, i.e., the separation of a target object from background in video, has made significant progress on real and challenging videos in recent years. To leverage this progress in 3D applications, thi…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Motion Prediction in Visual Object Tracking
Visual object tracking (VOT) is an essential component for many applications, such as autonomous driving or assistive robotics. However, recent works tend to develop accurate systems based on more computationally expensi…
Autonomous Drivingmotion predictionObjectObject Tracking+6Self-supervised Video Object Segmentation
The objective of this paper is self-supervised representation learning, with the goal of solving semi-supervised video object segmentation (a.k.a. dense tracking). We make the following contributions: (i) we propose to i…
ObjectOne-shot visual object segmentationRepresentation LearningSegmentation+4D3S - A Discriminative Single Shot Segmentation Tracker
Template-based discriminative trackers are currently the dominant tracking paradigm due to their robustness, but are restricted to bounding box tracking and a limited range of transformation models, which reduces their l…
ObjectObject TrackingSegmentationSemantic Segmentation+4ALBA : Reinforcement Learning for Video Object Segmentation
We consider the challenging problem of zero-shot video object segmentation (VOS). That is, segmenting and tracking multiple moving objects within a video fully automatically, without any manual initialization. We treat t…
ObjectOne-shot visual object segmentationreinforcement-learningReinforcement Learning+6