Papers One-shot visual object segmentation
“One-shot visual object segmentation” 태그가 달린 논문 41편 · 필터 해제
Associating Objects with Transformers for Video Object Segmentation
This paper investigates how to realize better and more efficient embedding learning to tackle the semi-supervised video object segmentation under challenging multi-object scenarios. The state-of-the-art methods learn to …
ObjectOne-shot visual object segmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+3Rethinking Cross-modal Interaction from a Top-down Perspective for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to segment video objects with the guidance of natural language reference. Previous methods typically tackle RVOS through directly grounding linguistic reference over the im…
ObjectOne-shot visual object segmentationReferring Video Object SegmentationSemantic Segmentation+2TransVOS: Video Object Segmentation with Transformers
Recently, Space-Time Memory Network (STM) based methods have achieved state-of-the-art performance in semi-supervised video object segmentation (VOS). A crucial problem in this task is how to model the dependency both am…
ObjectOne-shot visual object segmentationSegmentationSemantic Segmentation+3Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
Current state-of-the-art object detection and segmentation methods work well under the closed-world assumption. This closed-world setting assumes that the list of object categories is available during training and deploy…
Objectobject-detectionObject DetectionObject Tracking+4Learning Position and Target Consistency for Memory-based Video Object Segmentation
This paper studies the problem of semi-supervised video object segmentation(VOS). Multiple works have shown that memory-based approaches can be effective for video object segmentation. They are mostly based on pixel-leve…
ObjectOne-shot visual object segmentationPositionSegmentation+4Efficient Regional Memory Network for Video Object Segmentation
Recently, several Space-Time Memory based networks have shown that the object cues (e.g. video frames as well as the segmented object masks) from the past frames are useful for segmenting objects in the current frame. Ho…
ObjectOne-shot visual object segmentationOptical Flow EstimationSemantic Segmentation+3Separable Structure Modeling for Semi-supervised Video Object Segmentation
In this paper, we propose a separable structure modeling approach for semi-supervised video object segmentation. Unlike most existing methods which preclude the semantically structural information of target objects, our…
ObjectOne-shot visual object segmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation
In this paper we introduce a Transformer-based approach to video object segmentation (VOS). To address compounding error and scalability issues of prior work, we propose a scalable, end-to-end method for VOS called Spars…
Inductive BiasMotion SegmentationObjectOne-shot visual object segmentation+6Learning 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+2Spatiotemporal 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+5Delving 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+3Collaborative 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+3Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching
One-shot Video Object Segmentation~(VOS) is the task of pixel-wise tracking an object of interest within a video sequence, where the segmentation mask of the first frame is given at inference time. In recent years, Recur…
One-shot visual object segmentationSegmentationSemantic SegmentationVideo Object Segmentation+1PMVOS: 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+3URVOS: 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+5Proposal-based Video Completion
Video inpainting is an important technique for a wide variety of applications from video content editing to video restoration. Early approaches follow image inpainting paradigms, but are challenged by complex camera moti…
Image Inpaintingobject-detectionObject DetectionOne-shot visual object segmentation+2Self-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+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+6Learning 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+4