Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentation
Location and appearance are the key cues for video object segmentation. Many sources such as RGB, depth, optical flow and static saliency can provide useful information about the objects. However, existing approaches onl…
Depth EstimationObjectSalient Object DetectionUnsupervised Video Object Segmentation+2Joint Inductive and Transductive Learning for Video Object Segmentation
Semi-supervised video object segmentation is a task of segmenting the target object in a video sequence given only a mask annotation in the first frame. The limited information available makes it an extremely challenging…
Inductive LearningObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+3Full-Duplex Strategy for Video Object Segmentation
Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across these two cues. In this work, we study a nov…
ObjectObject DetectionSalient Object DetectionSegmentation+6Self-Supervised Video Object Segmentation by Motion-Aware Mask Propagation
We propose a self-supervised spatio-temporal matching method, coined Motion-Aware Mask Propagation (MAMP), for video object segmentation. MAMP leverages the frame reconstruction task for training without the need for ann…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Accelerating Video Object Segmentation with Compressed Video
We propose an efficient plug-and-play acceleration framework for semi-supervised video object segmentation by exploiting the temporal redundancies in videos presented by the compressed bitstream. Specifically, we propose…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2MeNToS: Tracklets Association with a Space-Time Memory Network
We propose a method for multi-object tracking and segmentation (MOTS) that does not require fine-tuning or per benchmark hyperparameter selection. The proposed method addresses particularly the data association problem. …
Instance SegmentationMulti-Object TrackingMulti-Object Tracking and SegmentationObject+6Fast Pixel-Matching for Video Object Segmentation
Video object segmentation, aiming to segment the foreground objects given the annotation of the first frame, has been attracting increasing attentions. Many state-of-the-art approaches have achieved great performance by …
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationDo Different Tracking Tasks Require Different Appearance Models?
Tracking objects of interest in a video is one of the most popular and widely applicable problems in computer vision. However, with the years, a Cambrian explosion of use cases and benchmarks has fragmented the problem i…
Multi-Object TrackingMulti-Object Tracking and SegmentationMultiple People TrackingObject Tracking+10MSN: Efficient Online Mask Selection Network for Video Instance Segmentation
In this work we present a novel solution for Video Instance Segmentation(VIS), that is automatically generating instance level segmentation masks along with object class and tracking them in a video. Our method improves …
Instance SegmentationSegmentationSemantic SegmentationVideo Instance Segmentation+2Video Object Segmentation Using Global and Instance Embedding Learning
In this paper, we propose a feature embedding based video object segmentation (VOS) method which is simple, fast and effective. The current VOS task involves two main challenges: object instance differentiation and c…
ObjectRelationSegmentationSemantic Segmentation+2Delving Deep Into Many-to-Many Attention for Few-Shot Video Object Segmentation
This paper tackles the task of Few-Shot Video Object Segmentation (FSVOS), i.e., segmenting objects in the query videos with certain class specified in a few labeled support images. The key is to model the relationsh…
Meta-LearningSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationReciprocal Transformations for Unsupervised Video Object Segmentation
Unsupervised video object segmentation (UVOS) aims at segmenting the primary objects in videos without any human intervention. Due to the lack of prior knowledge about the primary objects, identifying them from video…
ObjectOptical Flow EstimationSemantic SegmentationUnsupervised Video Object Segmentation+2Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
This paper presents a simple yet effective approach to modeling space-time correspondences in the context of video object segmentation. Unlike most existing approaches, we establish correspondences directly between frame…
Semantic SegmentationSemi-Supervised Video Object SegmentationVideo Object SegmentationVideo Semantic SegmentationSynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation. However, collecting large datasets for these tasks is expensive in terms of …
Objectobject-detectionReferring Expression SegmentationSegmentation+1ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
Transformers have shown great potential in various computer vision tasks owing to their strong capability in modeling long-range dependency using the self-attention mechanism. Nevertheless, vision transformers treat an i…
Image ClassificationInductive BiasObject DetectionVideo Object SegmentationAssociating 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+3Polygonal Point Set Tracking
In this paper, we propose a novel learning-based polygonal point set tracking method. Compared to existing video object segmentation~(VOS) methods that propagate pixel-wise object mask information, we propagate a polygon…
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationAttention-guided Temporally Coherent Video Object Matting
This paper proposes a novel deep learning-based video object matting method that can achieve temporally coherent matting results. Its key component is an attention-based temporal aggregation module that maximizes image m…
Image MattingObjectSemantic SegmentationVideo Matting+2