Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Autoencoder-based background reconstruction and foreground segmentation with background noise estimation
Even after decades of research, dynamic scene background reconstruction and foreground object segmentation are still considered as open problems due various challenges such as illumination changes, camera movements, or b…
Foreground SegmentationSegmentationUnsupervised Video Object SegmentationVideo Background Subtraction+1Reliable Propagation-Correction Modulation for Video Object Segmentation
Error propagation is a general but crucial problem in online semi-supervised video object segmentation. We aim to suppress error propagation through a correction mechanism with high reliability. The key insight is to dis…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1End-to-End Referring Video Object Segmentation with Multimodal Transformers
The referring video object segmentation task (RVOS) involves segmentation of a text-referred object instance in the frames of a given video. Due to the complex nature of this multimodal task, which combines text reasonin…
Inductive BiasInstance SegmentationReferring Expression SegmentationReferring Video Object Segmentation+5MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation
The task of semi-supervised video object segmentation (VOS) has been greatly advanced and state-of-the-art performance has been made by dense matching-based methods. The recent methods leverage space-time memory (STM) ne…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Learning To Segment Dominant Object Motion From Watching Videos
Existing deep learning based unsupervised video object segmentation methods still rely on ground-truth segmentation masks to train. Unsupervised in this context only means that no annotated frames are used during inferen…
ObjectOptical Flow EstimationSegmentationSemantic Segmentation+3Hierarchical interaction network for video object segmentation from referring expressions
In this paper, we investigate the problem of video object segmentation from referring expressions (VOSRE). Conventional methods typically perform multi-modal fusion based on linguistic features and the visual features ex…
Optical Flow EstimationReferring Expression SegmentationSemantic SegmentationVideo Object Segmentation+1FlowVOS: Weakly-Supervised Visual Warping for Detail-Preserving and Temporally Consistent Single-Shot Video Object Segmentation
We consider the task of semi-supervised video object segmentation (VOS). Our approach mitigates shortcomings in previous VOS work by addressing detail preservation and temporal consistency using visual warping. In contra…
ObjectOptical Flow EstimationSegmentationSemantic Segmentation+3FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical Flow
Semi-supervised video object segmentation (VOS) aims to segment a few moving objects in a video sequence, where these objects are specified by annotation of first frame. The optical flow has been considered in many exist…
Optical Flow EstimationSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos
Despite receiving significant attention from the research community, the task of segmenting and tracking objects in monocular videos still has much room for improvement. Existing works have simultaneously justified the e…
SegmentationSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+2D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos
Despite receiving significant attention from the research community, the task of segmenting and tracking objects in monocular videos still has much room for improvement. Existing works have simultaneously justified the e…
Multi-Object Tracking and SegmentationSegmentationSemantic SegmentationUnsupervised Video Object Segmentation+4Dense Unsupervised Learning for Video Segmentation
We present a novel approach to unsupervised learning for video object segmentation (VOS). Unlike previous work, our formulation allows to learn dense feature representations directly in a fully convolutional regime. We r…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationUnsupervised Video Object Segmentation+3Video Salient Object Detection via Contrastive Features and Attention Modules
Video salient object detection aims to find the most visually distinctive objects in a video. To explore the temporal dependencies, existing methods usually resort to recurrent neural networks or optical flow. However, t…
Contrastive LearningObjectobject-detectionObject Detection+7Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic Perspective
Modern video object segmentation (VOS) algorithms have achieved remarkably high performance in a sequential processing order, while most of currently prevailing pipelines still show some obvious inadequacy like accumulat…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation
Video object segmentation (VOS) is an essential part of autonomous vehicle navigation. The real-time speed is very important for the autonomous vehicle algorithms along with the accuracy metric. In this paper, we propose…
Objectobject-detectionObject DetectionSemantic Segmentation+3Multi-Object Tracking and Segmentation with a Space-Time Memory Network
We propose a method for multi-object tracking and segmentation based on a novel memory-based mechanism to associate tracklets. The proposed tracker, MeNToS, addresses particularly the long-term data association problem, …
Instance SegmentationMulti-Object TrackingMulti-Object Tracking and SegmentationMultiple Object Tracking+9Pixel-Level Bijective Matching for Video Object Segmentation
Semi-supervised video object segmentation (VOS) aims to track the designated objects present in the initial frame of a video at the pixel level. To fully exploit the appearance information of an object, pixel-level featu…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Hierarchical Memory Matching Network for Video Object Segmentation
We present Hierarchical Memory Matching Network (HMMN) for semi-supervised video object segmentation. Based on a recent memory-based method [33], we propose two advanced memory read modules that enable us to perform memo…
ObjectRetrievalSemantic SegmentationSemi-Supervised Video Object Segmentation+2Space Time Recurrent Memory Network
Transformers have recently been popular for learning and inference in the spatial-temporal domain. However, their performance relies on storing and applying attention to the feature tensor of each frame in video. Hence, …
Semantic SegmentationVideo Object SegmentationVideo PredictionVideo Semantic SegmentationShifted Chunk Transformer for Spatio-Temporal Representational Learning
Spatio-temporal representational learning has been widely adopted in various fields such as action recognition, video object segmentation, and action anticipation. Previous spatio-temporal representational learning appro…
Action AnticipationAction Recognitionimage-classificationImage Classification+3VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
Lane detection plays a key role in autonomous driving. While car cameras always take streaming videos on the way, current lane detection works mainly focus on individual images (frames) by ignoring dynamics along the vid…
Autonomous DrivingLane DetectionSemantic SegmentationVideo Object Segmentation+1