Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
One-Shot Weakly Supervised Video Object Segmentation
Conventional few-shot object segmentation methods learn object segmentation from a few labelled support images with strongly labelled segmentation masks. Recent work has shown to perform on par with weaker levels of supe…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Automatic Video Object Segmentation via Motion-Appearance-Stream Fusion and Instance-aware Segmentation
This paper presents a method for automatic video object segmentation based on the fusion of motion stream, appearance stream, and instance-aware segmentation. The proposed scheme consists of a two-stream fusion network a…
Foreground SegmentationInstance SegmentationObjectSegmentation+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+3Learning to Track Any Object
Object tracking can be formulated as "finding the right object in a video". We observe that recent approaches for class-agnostic tracking tend to focus on the "finding" part, but largely overlook the "object" part of the…
Instance SegmentationObjectObject TrackingSemantic Segmentation+3Anchor Diffusion for Unsupervised Video Object Segmentation
Unsupervised video object segmentation has often been tackled by methods based on recurrent neural networks and optical flow. Despite their complexity, these kinds of approaches tend to favour short-term temporal depende…
Image SegmentationObjectOptical Flow EstimationSemantic Segmentation+3Illumination-Based Data Augmentation for Robust Background Subtraction
A core challenge in background subtraction (BGS) is handling videos with sudden illumination changes in consecutive frames. In this paper, we tackle the problem from a data point-of-view using data augmentation. Our meth…
Data AugmentationForeground SegmentationVideo Background SubtractionVideo Object SegmentationObject Segmentation Tracking from Generic Video Cues
We propose a light-weight variational framework for online tracking of object segmentations in videos based on optical flow and image boundaries. While high-end computer vision methods on this task rely on sequence speci…
ObjectOptical Flow EstimationRobot NavigationSemantic Segmentation+2AGSS-VOS: Attention Guided Single-Shot Video Object Segmentation
Most video object segmentation approaches process objects separately. This incurs high computational cost when multiple objects exist. In this paper, we propose AGSS-VOS to segment multiple objects in one feed-forward pa…
DecoderObjectOne-shot visual object segmentationSemantic Segmentation+3Fast Video Object Segmentation via Dynamic Targeting Network
We propose a new model for fast and accurate video object segmentation. It consists of two convolutional neural networks, a Dynamic Targeting Network (DTN) and a Mask Refinement Network (MRN). DTN locates the object by d…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Towards Good Practices for Video Object Segmentation
Semi-supervised video object segmentation is an interesting yet challenging task in machine learning. In this work, we conduct a series of refinements with the propagation-based video object segmentation method and empir…
BIG-bench Machine LearningObjectOne-shot visual object segmentationSegmentation+4CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
In this work we propose a capsule-based approach for semi-supervised video object segmentation. Current video object segmentation methods are frame-based and often require optical flow to capture temporal consistency acr…
ObjectOne-shot visual object segmentationOptical Flow EstimationSegmentation+5LIP: Learning Instance Propagation for Video Object Segmentation
In recent years, the task of segmenting foreground objects from background in a video, i.e. video object segmentation (VOS), has received considerable attention. In this paper, we propose a single end-to-end trainable de…
Data AugmentationInstance SegmentationObjectSegmentation+3EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency
The existing approaches for salient motion segmentation are unable to explicitly learn geometric cues and often give false detections on prominent static objects. We exploit multiview geometric constraints to avoid such …
Motion SegmentationOptical Flow EstimationUnsupervised Video Object SegmentationVideo Object SegmentationRPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation
In this paper, we introduce a self-supervised approach for video object segmentation without human labeled data.Specifically, we present Robust Pixel-level Matching Net-works (RPM-Net), a novel deep architecture that mat…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation
This paper tackles the problem of video object segmentation. We are specifically concerned with the task of segmenting all pixels of a target object in all frames, given the annotation mask in the first frame. Even when …
FormMeta-LearningObjectScene Understanding+3Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning
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. The challenges lie in how to onli…
reinforcement-learningReinforcement LearningReinforcement Learning (RL)Segmentation+4DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
In this paper, we propose the differentiable mask-matching network (DMM-Net) for solving the video object segmentation problem where the initial object masks are provided. Relying on the Mask R-CNN backbone, we extract m…
ObjectOne-shot visual object segmentationRolling Shutter CorrectionSemantic Segmentation+3Fast Video Object Segmentation via Mask Transfer Network
Accuracy and processing speed are two important factors that affect the use of video object segmentation (VOS) in real applications. With the advanced techniques of deep neural networks, the accuracy has been significant…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationIn defense of OSVOS
As a milestone for video object segmentation, one-shot video object segmentation (OSVOS) has achieved a large margin compared to the conventional optical-flow based methods regarding to the segmentation accuracy. Its exc…
Depth EstimationObjectOptical Flow EstimationSaliency Detection+5RANet: Ranking Attention Network for Fast Video Object Segmentation
Despite online learning (OL) techniques have boosted the performance of semi-supervised video object segmentation (VOS) methods, the huge time costs of OL greatly restrict their practicality. Matching based and propagati…
DecoderObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2