Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Implicit Motion-Compensated Network for Unsupervised Video Object Segmentation
Unsupervised video object segmentation (UVOS) aims at automatically separating the primary foreground object(s) from the background in a video sequence. Existing UVOS methods either lack robustness when there are visuall…
Motion CompensationSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1In-N-Out Generative Learning for Dense Unsupervised Video Segmentation
In this paper, we focus on unsupervised learning for Video Object Segmentation (VOS) which learns visual correspondence (i.e., the similarity between pixel-level features) from unlabeled videos. Previous methods are main…
Contrastive LearningSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+2Temporal Transductive Inference for Few-Shot Video Object Segmentation
Few-shot video object segmentation (FS-VOS) aims at segmenting video frames using a few labelled examples of classes not seen during initial training. In this paper, we present a simple but effective temporal transductiv…
Meta-LearningObjectSemantic SegmentationVideo Object Segmentation+1Video Polyp Segmentation: A Deep Learning Perspective
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era. Over the years, developments in VPS are not moving forward with ease due to the lack of large-scale fine-grained segmentat…
AttributeDeep LearningSegmentationSemantic Segmentation+3Scalable Video Object Segmentation with Identification Mechanism
This paper delves into the challenges of achieving scalable and effective multi-object modeling for semi-supervised Video Object Segmentation (VOS). Previous VOS methods decode features with a single positive object, lim…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Robust Visual Tracking by Segmentation
Estimating the target extent poses a fundamental challenge in visual object tracking. Typically, trackers are box-centric and fully rely on a bounding box to define the target in the scene. In practice, objects often hav…
DecoderObject TrackingSegmentationSemantic Segmentation+5Local-Global Context Aware Transformer for Language-Guided Video Segmentation
We explore the task of language-guided video segmentation (LVS). Previous algorithms mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context and easily suffering from visual-linguistic…
Referring Expression SegmentationReferring Video Object SegmentationSegmentationSemantic Segmentation+4End-to-End Semi-Supervised Learning for Video Action Detection
In this work, we focus on semi-supervised learning for video action detection which utilizes both labeled as well as unlabeled data. We propose a simple end-to-end consistency based approach which effectively utilizes th…
Action DetectionClassification ConsistencySemantic SegmentationSemi-Supervised Video Action Detection+4Revisiting Click-based Interactive Video Object Segmentation
While current methods for interactive Video Object Segmentation (iVOS) rely on scribble-based interactions to generate precise object masks, we propose a Click-based interactive Video Object Segmentation (CiVOS) framewor…
Interactive Video Object SegmentationObjectSegmentationSemantic Segmentation+2Box Supervised Video Segmentation Proposal Network
Video Object Segmentation (VOS) has been targeted by various fully-supervised and self-supervised approaches. While fully-supervised methods demonstrate excellent results, self-supervised ones, which do not use pixel-lev…
Image SegmentationMotion CompensationObjectSegmentation+4Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks
Traditional media coding schemes typically encode image/video into a semantic-unknown binary stream, which fails to directly support downstream intelligent tasks at the bitstream level. Semantically Structured Image Codi…
Action RecognitionObjectobject-detectionObject Detection+6Learning Pixel Trajectories with Multiscale Contrastive Random Walks
A range of video modeling tasks, from optical flow to multiple object tracking, share the same fundamental challenge: establishing space-time correspondence. Yet, approaches that dominate each space differ. We take a ste…
Multiple Object TrackingObjectObject TrackingOptical Flow Estimation+4Language as Queries for Referring Video Object Segmentation
Referring video object segmentation (R-VOS) is an emerging cross-modal task that aims to segment the target object referred by a language expression in all video frames. In this work, we propose a simple and unified fram…
ObjectObject TrackingReferring Expression SegmentationReferring Video Object Segmentation+4YouMVOS: An Actor-Centric Multi-Shot Video Object Segmentation Dataset
Many video understanding tasks require analyzing multi-shot videos, but existing datasets for video object segmentation (VOS) only consider single-shot videos. To address this challenge, we collected a new dataset---…
ManagementSegmentationSemantic SegmentationVideo Object Segmentation+3Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross-Modal Denoising Networks
Audio-Guided video semantic segmentation is a challenging problem in visual analysis and editing, which automatically separates foreground objects from background in a video sequence according to the referring audio …
DecoderDenoisingSegmentationSemantic Segmentation+2Multi-Level Representation Learning With Semantic Alignment for Referring Video Object Segmentation
Referring video object segmentation (RVOS) is a challenging language-guided video grounding task, which requires comprehensively understanding the semantic information of both video content and language queries for o…
ObjectReferring Expression SegmentationReferring Video Object SegmentationRepresentation Learning+5Siamese Network with Interactive Transformer for Video Object Segmentation
Semi-supervised video object segmentation (VOS) refers to segmenting the target object in remaining frames given its annotation in the first frame, which has been actively studied in recent years. The key challenge lies …
DecoderObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2Iteratively Selecting an Easy Reference Frame Makes Unsupervised Video Object Segmentation Easier
Unsupervised video object segmentation (UVOS) is a per-pixel binary labeling problem which aims at separating the foreground object from the background in the video without using the ground truth (GT) mask of the foregro…
ObjectSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1A Discriminative Single-Shot Segmentation Network for Visual Object Tracking
Template-based discriminative trackers are currently the dominant tracking paradigm due to their robustness, but are restricted to bounding box tracking and a limited range of transformation models, which reduces their l…
ObjectObject TrackingSegmentationSemantic Segmentation+3HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images
Existing state-of-the-art methods for Video Object Segmentation (VOS) learn low-level pixel-to-pixel correspondences between frames to propagate object masks across video. This requires a large amount of densely annotate…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic Segmentation