Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Boosting Video Object Segmentation via Space-time Correspondence Learning
Current top-leading solutions for video object segmentation (VOS) typically follow a matching-based regime: for each query frame, the segmentation mask is inferred according to its correspondence to previously processed …
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Segment Everything Everywhere All at Once
In this work, we present SEEM, a promptable and interactive model for segmenting everything everywhere all at once in an image, as shown in Fig.1. In SEEM, we propose a novel decoding mechanism that enables diverse promp…
AllDecoderImage SegmentationInteractive Segmentation+5MED-VT++: Unifying Multimodal Learning with a Multiscale Encoder-Decoder Video Transformer
In this paper, we present an end-to-end trainable unified multiscale encoder-decoder transformer that is focused on dense prediction tasks in video. The presented Multiscale Encoder-Decoder Video Transformer (MED-VT) use…
Action SegmentationDecoderOptical Flow EstimationSegmentation+5CLVOS23: A Long Video Object Segmentation Dataset for Continual Learning
Continual learning in real-world scenarios is a major challenge. A general continual learning model should have a constant memory size and no predefined task boundaries, as is the case in semi-supervised Video Object Seg…
Continual LearningSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Co-attention Propagation Network for Zero-Shot Video Object Segmentation
Zero-shot video object segmentation (ZS-VOS) aims to segment foreground objects in a video sequence without prior knowledge of these objects. However, existing ZS-VOS methods often struggle to distinguish between foregro…
DecoderOptical Flow EstimationSemantic SegmentationVideo Object Segmentation+2SegGPT: Segmenting Everything In Context
We present SegGPT, a generalist model for segmenting everything in context. We unify various segmentation tasks into a generalist in-context learning framework that accommodates different kinds of segmentation data by tr…
Few-Shot Semantic SegmentationIn-Context LearningPanoptic SegmentationPersonalized Segmentation+4DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks
In this paper, we study masked autoencoder (MAE) pretraining on videos for matching-based downstream tasks, including visual object tracking (VOT) and video object segmentation (VOS). A simple extension of MAE is to rand…
DiversityObject TrackingSemantic SegmentationVideo Object Segmentation+2Reliability-Hierarchical Memory Network for Scribble-Supervised Video Object Segmentation
This paper aims to solve the video object segmentation (VOS) task in a scribble-supervised manner, in which VOS models are not only trained by the sparse scribble annotations but also initialized with the sparse target s…
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationCrOC: Cross-View Online Clustering for Dense Visual Representation Learning
Learning dense visual representations without labels is an arduous task and more so from scene-centric data. We propose to tackle this challenging problem by proposing a Cross-view consistency objective with an Online Cl…
ClusteringOnline ClusteringRepresentation LearningSegmentation+4Two-shot Video Object Segmentation
Previous works on video object segmentation (VOS) are trained on densely annotated videos. Nevertheless, acquiring annotations in pixel level is expensive and time-consuming. In this work, we demonstrate the feasibility …
ObjectPseudo LabelSegmentationSemantic Segmentation+3Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation
Static and moving objects often occur in real-life videos. Most video object segmentation methods only focus on extracting and exploiting motion cues to perceive moving objects. Once faced with the frames of static objec…
ObjectOptical Flow EstimationSemantic SegmentationUnsupervised Video Object Segmentation+3Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation
The objective of this paper is self-supervised learning of video object segmentation. We develop a unified framework which simultaneously models cross-frame dense correspondence for locally discriminative feature learnin…
SegmentationSelf-Supervised LearningSemantic SegmentationVideo Object Segmentation+2Guided Slot Attention for Unsupervised Video Object Segmentation
Unsupervised video object segmentation aims to segment the most prominent object in a video sequence. However, the existence of complex backgrounds and multiple foreground objects make this task challenging. To address t…
ObjectSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation
This paper tackles the problem of semi-supervised video object segmentation on resource-constrained devices, such as mobile phones. We formulate this problem as a distillation task, whereby we demonstrate that small spac…
Contrastive LearningKnowledge DistillationRepresentation LearningSemantic Segmentation+3Tsanet: Temporal and Scale Alignment for Unsupervised Video Object Segmentation
Unsupervised Video Object Segmentation (UVOS) refers to the challenging task of segmenting the prominent object in videos without manual guidance. In recent works, two approaches for UVOS have been discussed that can be …
DecoderObjectOptical Flow EstimationSemantic Segmentation+3One-Shot Video Inpainting
Recently, removing objects from videos and filling in the erased regions using deep video inpainting (VI) algorithms has attracted considerable attention. Usually, a video sequence and object segmentation masks for all f…
ObjectSegmentationSemantic SegmentationVideo Inpainting+2Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction
We introduce a novel robotic system for improving unseen object instance segmentation in the real world by leveraging long-term robot interaction with objects. Previous approaches either grasp or push an object and then …
Instance SegmentationMulti-Object TrackingObjectObject Tracking+6MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
Video object segmentation (VOS) aims at segmenting a particular object throughout the entire video clip sequence. The state-of-the-art VOS methods have achieved excellent performance (e.g., 90+% J&F) on existing datasets…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Maximal Cliques on Multi-Frame Proposal Graph for Unsupervised Video Object Segmentation
Unsupervised Video Object Segmentation (UVOS) aims at discovering objects and tracking them through videos. For accurate UVOS, we observe if one can locate precise segment proposals on key frames, subsequent processes ar…
Instance SegmentationObjectSegmentationSemantic Segmentation+4Flow-guided Semi-supervised Video Object Segmentation
We propose an optical flow-guided approach for semi-supervised video object segmentation. Optical flow is usually exploited as additional guidance information in unsupervised video object segmentation. However, its relev…
DecoderObjectOptical Flow EstimationSegmentation+5