Papers Semi-Supervised Video Object Segmentation
“Semi-Supervised Video Object Segmentation” 태그가 달린 논문 154편 · 필터 해제
Video Object Segmentation With Dynamic Memory Networks and Adaptive Object Alignment
In this paper, we propose a novel solution for object-matching based semi-supervised video object segmentation, where the target object masks in the first frame are provided. Existing object-matching based methods fo…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation
Current state-of-the-art approaches for Semi-supervised Video Object Segmentation (Semi-VOS) propagates information from previous frames to generate segmentation mask for the current frame. This results in high-quality s…
One-shot visual object segmentationSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Visual object tracking aims to precisely estimate the bounding box for the given target, which is a challenging problem due to factors such as deformation and occlusion. Many recent trackers adopt the multiple-stage trac…
Object TrackingSemi-Supervised Video Object SegmentationVisual Object TrackingSpatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation
This paper addresses the task of segmenting class-agnostic objects in semi-supervised setting. Although previous detection based methods achieve relatively good performance, these approaches extract the best proposal by …
Graph Neural NetworkObjectOne-shot visual object segmentationSemantic Segmentation+3Make One-Shot Video Object Segmentation Efficient Again
Video object segmentation (VOS) describes the task of segmenting a set of objects in each frame of a video. In the semi-supervised setting, the first mask of each object is provided at test time. Following the one-shot p…
Objectobject-detectionObject DetectionOne-shot visual object segmentation+5TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency Loss
Semi-supervised video object segmentation (semi-VOS) is widely used in many applications. This task is tracking class-agnostic objects from a given target mask. For doing this, various approaches have been developed base…
ObjectObject LocalizationOptical Flow EstimationSemantic Segmentation+4Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation
In this paper, we address several inadequacies of current video object segmentation pipelines. Firstly, a cyclic mechanism is incorporated to the standard semi-supervised process to produce more robust representations. B…
ObjectOne-shot visual object segmentationSegmentationSemantic Segmentation+3Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
We propose a new matching-based framework for semi-supervised video object segmentation (VOS). Recently, state-of-the-art VOS performance has been achieved by matching-based algorithms, in which feature banks are created…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Collaborative Video Object Segmentation by Multi-Scale Foreground-Background Integration
This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation. Unlike previous practices that focus on exploring the embedding learning of foreground obj…
ObjectOne-shot visual object segmentationSegmentationSemantic Segmentation+3PMVOS: Pixel-Level Matching-Based Video Object Segmentation
Semi-supervised video object segmentation (VOS) aims to segment arbitrary target objects in video when the ground truth segmentation mask of the initial frame is provided. Due to this limitation of using prior knowledge …
ObjectOne-shot visual object segmentationSegmentationSemantic Segmentation+3LSMVOS: Long-Short-Term Similarity Matching for Video Object
Objective Semi-supervised video object segmentation refers to segmenting the object in subsequent frames given the object label in the first frame. Existing algorithms are mostly based on the objectives of matching and p…
ObjectOptical Flow EstimationSegmentationSemantic Segmentation+3RPT: Learning Point Set Representation for Siamese Visual Tracking
While remarkable progress has been made in robust visual tracking, accurate target state estimation still remains a highly challenging problem. In this paper, we argue that this issue is closely related to the prevalent …
Semi-Supervised Video Object SegmentationState EstimationVisual TrackingKernelized 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+1Fast 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+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+4Fast 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+3Learning 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+3Learning 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+5