Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
In Defense of Online Models for Video Instance Segmentation
In recent years, video instance segmentation (VIS) has been largely advanced by offline models, while online models gradually attracted less attention possibly due to their inferior performance. However, online methods h…
Contrastive LearningInstance SegmentationSegmentationSemantic Segmentation+3Semantic-Aware Fine-Grained Correspondence
Establishing visual correspondence across images is a challenging and essential task. Recently, an influx of self-supervised methods have been proposed to better learn representations for visual correspondence. However, …
Pose TrackingSelf-Supervised LearningSemantic correspondenceSemantic Segmentation+2Region Aware Video Object Segmentation with Deep Motion Modeling
Current semi-supervised video object segmentation (VOS) methods usually leverage the entire features of one frame to predict object masks and update memory. This introduces significant redundant computations. To reduce r…
DecoderObjectSegmentationSemantic Segmentation+3Hierarchical Feature Alignment Network for Unsupervised Video Object Segmentation
Optical flow is an easily conceived and precious cue for advancing unsupervised video object segmentation (UVOS). Most of the previous methods directly extract and fuse the motion and appearance features for segmenting t…
ObjectOptical Flow EstimationSemantic SegmentationUnsupervised Video Object Segmentation+3Learning Quality-aware Dynamic Memory for Video Object Segmentation
Recently, several spatial-temporal memory-based methods have verified that storing intermediate frames and their masks as memory are helpful to segment target objects in videos. However, they mainly focus on better match…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
We present XMem, a video object segmentation architecture for long videos with unified feature memory stores inspired by the Atkinson-Shiffrin memory model. Prior work on video object segmentation typically only uses one…
2D Human Pose Estimation2D Object Detection3D Absolute Human Pose EstimationSegmentation+4Tackling Background Distraction in Video Object Segmentation
Semi-supervised video object segmentation (VOS) aims to densely track certain designated objects in videos. One of the main challenges in this task is the existence of background distractors that appear similar to the ta…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1SiamMask: A Framework for Fast Online Object Tracking and Segmentation
In this paper we introduce SiamMask, a framework to perform both visual object tracking and video object segmentation, in real-time, with the same simple method. We improve the offline training procedure of popular fully…
Multiple Object TrackingObjectObject TrackingSegmentation+4Towards Robust Referring Video Object Segmentation with Cyclic Relational Consensus
Referring Video Object Segmentation (R-VOS) is a challenging task that aims to segment an object in a video based on a linguistic expression. Most existing R-VOS methods have a critical assumption: the object referred to…
Referring Expression SegmentationReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+1Towards Robust Video Object Segmentation with Adaptive Object Calibration
In the booming video era, video segmentation attracts increasing research attention in the multimedia community. Semi-supervised video object segmentation (VOS) aims at segmenting objects in all target frames of a video,…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+4The Second Place Solution for The 4th Large-scale Video Object Segmentation Challenge--Track 3: Referring Video Object Segmentation
The referring video object segmentation task (RVOS) aims to segment object instances in a given video referred by a language expression in all video frames. Due to the requirement of understanding cross-modal semantics w…
Objectobject-detectionObject DetectionReferring Video Object Segmentation+55th Place Solution for YouTube-VOS Challenge 2022: Video Object Segmentation
Video object segmentation (VOS) has made significant progress with the rise of deep learning. However, there still exist some thorny problems, for example, similar objects are easily confused and tiny objects are difficu…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation
Referring video object segmentation aims to predict foreground labels for objects referred by natural language expressions in videos. Previous methods either depend on 3D ConvNets or incorporate additional 2D ConvNets as…
DenoisingReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+1A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic Information
Deep spatiotemporal models are used in a variety of computer vision tasks, such as action recognition and video object segmentation. Currently, there is a limited understanding of what information is captured by these mo…
Action RecognitionSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationDifferentiable Soft-Masked Attention
Transformers have become prevalent in computer vision due to their performance and flexibility in modelling complex operations. Of particular significance is the 'cross-attention' operation, which allows a vector represe…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Collaborative Attention Memory Network for Video Object Segmentation
Semi-supervised video object segmentation is a fundamental yet Challenging task in computer vision. Embedding matching based CFBI series networks have achieved promising results by foreground-background integration appro…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Recurrent Dynamic Embedding for Video Object Segmentation
Space-time memory (STM) based video object segmentation (VOS) networks usually keep increasing memory bank every several frames, which shows excellent performance. However, 1) the hardware cannot withstand the ever-incre…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Boosting Video Object Segmentation based on Scale Inconsistency
We present a refinement framework to boost the performance of pre-trained semi-supervised video object segmentation (VOS) models. Our work is based on scale inconsistency, which is motivated by the observation that exist…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Self-Supervised Video Object Segmentation via Cutout Prediction and Tagging
We propose a novel self-supervised Video Object Segmentation (VOS) approach that strives to achieve better object-background discriminability for accurate object segmentation. Distinct from previous self-supervised VOS m…
ObjectSegmentationSemantic SegmentationTAG+2Adaptive Memory Management for Video Object Segmentation
Matching-based networks have achieved state-of-the-art performance for video object segmentation (VOS) tasks by storing every-k frames in an external memory bank for future inference. Storing the intermediate frames' pre…
ManagementObjectSegmentationSemantic Segmentation+3