Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation
Domain shift has always been one of the primary issues in video object segmentation (VOS), for which models suffer from degeneration when tested on unfamiliar datasets. Recently, many online methods have emerged to narro…
Domain AdaptationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
Previous cycle-consistency correspondence learning methods usually leverage image patches for training. In this paper, we present a fully convolutional method, which is simpler and more coherent to the inference process.…
Landmark TrackingPose TrackingSemantic SegmentationVideo Object Segmentation+1Emerging Properties in Self-Supervised Vision Transformers
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets). Beyond the fact that adapting self-supervised metho…
Copy DetectionImage ClassificationImage RetrievalLinear evaluation+7Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps
We propose a novel guided interactive segmentation (GIS) algorithm for video objects to improve the segmentation accuracy and reduce the interaction time. First, we design the reliability-based attention module to analyz…
Interactive SegmentationInteractive Video Object SegmentationSegmentationSemantic Segmentation+2Self-supervised Video Object Segmentation by Motion Grouping
Animals have evolved highly functional visual systems to understand motion, assisting perception even under complex environments. In this paper, we work towards developing a computer vision system able to segment objects…
Motion SegmentationObjectOptical Flow EstimationSemantic Segmentation+4Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation
This paper addresses the task of unsupervised video multi-object segmentation. Current approaches follow a two-stage paradigm: 1) detect object proposals using pre-trained Mask R-CNN, and 2) conduct generic feature match…
ObjectObject DiscoverySegmentationSemantic Segmentation+2Learning 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+4Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
Learning a good representation for space-time correspondence is the key for various computer vision tasks, including tracking object bounding boxes and performing video object pixel segmentation. To learn generalizable r…
Contrastive LearningObjectObject TrackingSegmentation+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+3Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild
This paper proposes a framework for the interactive video object segmentation (VOS) in the wild where users can choose some frames for annotations iteratively. Then, based on the user annotations, a segmentation algorith…
Deep Reinforcement LearningInteractive Video Object SegmentationVideo Object SegmentationModular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion
We present Modular interactive VOS (MiVOS) framework which decouples interaction-to-mask and mask propagation, allowing for higher generalizability and better performance. Trained separately, the interaction module conve…
Interactive Video Object SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Triple-cooperative Video Shadow Detection
Shadow detection in a single image has received significant research interest in recent years. However, much fewer works have been explored in shadow detection over dynamic scenes. The bottleneck is the lack of a well-es…
Saliency DetectionSemantic SegmentationShadow DetectionVideo Object Segmentation+2Fast Interactive Video Object Segmentation with Graph Neural Networks
Pixelwise annotation of image sequences can be very tedious for humans. Interactive video object segmentation aims to utilize automatic methods to speed up the process and reduce the workload of the annotators. Most cont…
Graph Neural NetworkInteractive Video Object SegmentationObjectSemantic Segmentation+2Separable 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+1SwiftNet: Real-time Video Object Segmentation
In this work we present SwiftNet for real-time semisupervised video object segmentation (one-shot VOS), which reports 77.8% J &F and 70 FPS on DAVIS 2017 validation dataset, leading all present solutions in overall accur…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Active Boundary Loss for Semantic Segmentation
This paper proposes a novel active boundary loss for semantic segmentation. It can progressively encourage the alignment between predicted boundaries and ground-truth boundaries during end-to-end training, which is not e…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationSSTVOS: 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+6VideoClick: Video Object Segmentation with a Single Click
Annotating videos with object segmentation masks typically involves a two stage procedure of drawing polygons per object instance for all the frames and then linking them through time. While simple, this is a very tediou…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos
Segmenting objects in videos is a fundamental computer vision task. The current deep learning based paradigm offers a powerful, but data-hungry solution. However, current datasets are limited by the cost and human effort…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Mask Selection and Propagation for Unsupervised Video Object Segmentation
In this work we present a novel approach for Unsupervised Video Object Segmentation, that is automatically generating instance level segmentation masks for salient objects and tracking them in a video. We efficiently han…
SegmentationSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1