Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
FODVid: Flow-guided Object Discovery in Videos
Segmentation of objects in a video is challenging due to the nuances such as motion blurring, parallax, occlusions, changes in illumination, etc. Instead of addressing these nuances separately, we focus on building a gen…
ObjectObject DiscoveryObject Discovery In VideosSegmentation+3ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: Semi-Supervised Video Object Segmentation
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object segmentation. In this study, we introduce MSDeAOT, a variant of the AO…
ObjectPositionSegmentationSemantic Segmentation+3ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: TREK-150 Single Object Tracking
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object tracking and segmentation. In this study, we convert the bounding boxe…
ObjectObject TrackingSegmentationSemantic Segmentation+3RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation
The Segment Anything Model (SAM) has gained significant attention for its impressive performance in image segmentation. However, it lacks proficiency in referring video object segmentation (RVOS) due to the need for prec…
Image SegmentationReferring ExpressionReferring Video Object SegmentationSegmentation+3Segment Anything Meets Point Tracking
The Segment Anything Model (SAM) has established itself as a powerful zero-shot image segmentation model, enabled by efficient point-centric annotation and prompt-based models. While click and brush interactions are both…
Interactive Video Object SegmentationObjectPoint TrackingSegmentation+4Bidirectional Correlation-Driven Inter-Frame Interaction Transformer for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to segment the target object in a video sequence described by a language expression. Typical multimodal Transformer based RVOS approaches process video sequence in a frame-…
ObjectReferring Video Object SegmentationRepresentation LearningSegmentation+3TrickVOS: A Bag of Tricks for Video Object Segmentation
Space-time memory (STM) network methods have been dominant in semi-supervised video object segmentation (SVOS) due to their remarkable performance. In this work, we identify three key aspects where we can improve such me…
DecoderObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2Online Unsupervised Video Object Segmentation via Contrastive Motion Clustering
Online unsupervised video object segmentation (UVOS) uses the previous frames as its input to automatically separate the primary object(s) from a streaming video without using any further manual annotation. A major chall…
ClusteringContrastive LearningObjectOptical Flow Estimation+5LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to segment the target instance referred by a given text expression in a video clip. The text expression normally contains sophisticated description of the instance's appear…
Referring Expression SegmentationReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+1SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
This paper studies referring video object segmentation (RVOS) by boosting video-level visual-linguistic alignment. Recent approaches model the RVOS task as a sequence prediction problem and perform multi-modal interactio…
cross-modal alignmentObjectReferring Expression SegmentationReferring Video Object Segmentation+4Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation
Recently, video object segmentation (VOS) referred by multi-modal signals, e.g., language and audio, has evoked increasing attention in both industry and academia. It is challenging for exploring the semantic alignment w…
ObjectReferring Expression SegmentationReferring Video Object SegmentationSemantic Segmentation+2AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras
Depth cameras have found applications in diverse fields, such as computer vision, artificial intelligence, and video gaming. However, the high latency and low frame rate of existing commodity depth cameras impose limitat…
Depth EstimationGPUOptical Flow EstimationSemantic Segmentation+2Siamese Masked Autoencoders
Establishing correspondence between images or scenes is a significant challenge in computer vision, especially given occlusions, viewpoint changes, and varying object appearances. In this paper, we present Siamese Masked…
Data AugmentationDecoderObjectSemantic Segmentation+2READMem: Robust Embedding Association for a Diverse Memory in Unconstrained Video Object Segmentation
We present READMem (Robust Embedding Association for a Diverse Memory), a modular framework for semi-automatic video object segmentation (sVOS) methods designed to handle unconstrained videos. Contemporary sVOS works typ…
Semantic SegmentationSemi-Supervised Video Object SegmentationVideo Object SegmentationVideo Semantic SegmentationUVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model
The current state-of-the-art methods for unsupervised video object segmentation (UVOS) require extensive training on video datasets with mask annotations, limiting their effectiveness in handling challenging scenarios. H…
Image SegmentationObjectObject TrackingSegmentation+4Video Object Segmentation in Panoptic Wild Scenes
In this paper, we introduce semi-supervised video object segmentation (VOS) to panoptic wild scenes and present a large-scale benchmark as well as a baseline method for it. Previous benchmarks for VOS with sparse annotat…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Personalize Segment Anything Model with One Shot
Driven by large-data pre-training, Segment Anything Model (SAM) has been demonstrated as a powerful and promptable framework, revolutionizing the segmentation models. Despite the generality, customizing SAM for specific …
Image GenerationmodelPersonalized SegmentationSegmentation+5Event-Free Moving Object Segmentation from Moving Ego Vehicle
Moving object segmentation (MOS) in dynamic scenes is an important, challenging, but under-explored research topic for autonomous driving, especially for sequences obtained from moving ego vehicles. Most segmentation met…
Autonomous DrivingBenchmarkingObjectOptical Flow Estimation+5Robust and Efficient Memory Network for Video Object Segmentation
This paper proposes a Robust and Efficient Memory Network, referred to as REMN, for studying semi-supervised video object segmentation (VOS). Memory-based methods have recently achieved outstanding VOS performance by per…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping
We study learning object segmentation from unlabeled videos. Humans can easily segment moving objects without knowing what they are. The Gestalt law of common fate, i.e., what move at the same speed belong together, has …
Motion SegmentationObjectObject DiscoveryOptical Flow Estimation+6