Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Depth-aware Test-Time Training for Zero-shot Video Object Segmentation
Zero-shot Video Object Segmentation (ZSVOS) aims at segmenting the primary moving object without any human annotations. Mainstream solutions mainly focus on learning a single model on large-scale video datasets, which st…
Depth EstimationDepth PredictionSemantic SegmentationVideo Object Segmentation+2VideoMAC: Video Masked Autoencoders Meet ConvNets
Recently, the advancement of self-supervised learning techniques, like masked autoencoders (MAE), has greatly influenced visual representation learning for images and videos. Nevertheless, it is worth noting that the pre…
Pose TrackingRepresentation LearningSelf-Supervised LearningSemantic Segmentation+2UniVS: Unified and Universal Video Segmentation with Prompts as Queries
Despite the recent advances in unified image segmentation (IS), developing a unified video segmentation (VS) model remains a challenge. This is mainly because generic category-specified VS tasks need to detect all object…
DecoderReferring Expression SegmentationReferring Video Object SegmentationVideo Instance Segmentation+6Lester: rotoscope animation through video object segmentation and tracking
This article introduces Lester, a novel method to automatically synthetise retro-style 2D animations from videos. The method approaches the challenge mainly as an object segmentation and tracking problem. Video frames ar…
3D Human Pose EstimationObjectPose EstimationSemantic Segmentation+3Moving Object Proposals with Deep Learned Optical Flow for Video Object Segmentation
Dynamic scene understanding is one of the most conspicuous field of interest among computer vision community. In order to enhance dynamic scene understanding, pixel-wise segmentation with neural networks is widely accept…
DecoderObjectOptical Flow EstimationScene Understanding+3Point-VOS: Pointing Up Video Object Segmentation
Current state-of-the-art Video Object Segmentation (VOS) methods rely on dense per-object mask annotations both during training and testing. This requires time-consuming and costly video annotation mechanisms. We propose…
ObjectSemantic SegmentationVideo Narrative GroundingVideo Object Segmentation+1Is Two-shot All You Need? A Label-efficient Approach for Video Segmentation in Breast Ultrasound
Breast lesion segmentation from breast ultrasound (BUS) videos could assist in early diagnosis and treatment. Existing video object segmentation (VOS) methods usually require dense annotation, which is often inaccessible…
AllLesion SegmentationSegmentationSemantic Segmentation+3Vivim: a Video Vision Mamba for Medical Video Segmentation
Medical video segmentation gains increasing attention in clinical practice due to the redundant dynamic references in video frames. However, traditional convolutional neural networks have a limited receptive field and tr…
Lesion SegmentationMambaSegmentationSemantic Segmentation+3Self-supervised Video Object Segmentation with Distillation Learning of Deformable Attention
Video object segmentation is a fundamental research problem in computer vision. Recent techniques have often applied attention mechanism to object representation learning from video sequences. However, due to temporal ch…
Knowledge DistillationObjectRepresentation LearningSegmentation+4Explore Synergistic Interaction Across Frames for Interactive Video Object Segmentation
Interactive Video Object Segmentation (iVOS) is a challenging task that requires real-time human-computer interaction. To improve the user experience, it is important to consider the user's input habits, segmentation qua…
Interactive Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationUnderstanding Video Transformers via Universal Concept Discovery
This paper studies the problem of concept-based interpretability of transformer representations for videos. Concretely, we seek to explain the decision-making process of video transformers based on high-level, spatiotemp…
Action RecognitionDecision MakingFine-grained Action RecognitionSemantic Segmentation+2OMG-Seg: Is One Model Good Enough For All Segmentation?
In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models. We propose OMG-Seg, One Model that is Good enough to efficiently and effectively handle all the seg…
AllDecoderInteractive SegmentationPanoptic Segmentation+41st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation
The recent transformer-based models have dominated the Referring Video Object Segmentation (RVOS) task due to the superior performance. Most prior works adopt unified DETR framework to generate segmentation masks in quer…
ObjectReferring Video Object SegmentationSegmentationSemantic Segmentation+2Learning to Segment Referred Objects from Narrated Egocentric Videos
Egocentric videos provide a first-person perspective of the wearer's activities involving simultaneous interactions with multiple objects. In this work we propose the task of weakly-supervised Narration-based Video O…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Tracking with Human-Intent Reasoning
Advances in perception modeling have significantly improved the performance of object tracking. However, the current methods for specifying the target object in the initial frame are either by 1) using a box or mask temp…
Language ModellingObjectObject TrackingReferring Video Object Segmentation+3UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces
The reference-based object segmentation tasks, namely referring image segmentation (RIS), few-shot image segmentation (FSS), referring video object segmentation (RVOS), and video object segmentation (VOS), aim to segment…
Image SegmentationObjectReferring Expression SegmentationReferring Video Object Segmentation+4No More Shortcuts: Realizing the Potential of Temporal Self-Supervision
Self-supervised approaches for video have shown impressive results in video understanding tasks. However, unlike early works that leverage temporal self-supervision, current state-of-the-art methods primarily rely on tas…
Action ClassificationAttributeContrastive LearningPose Tracking+5Hierarchical Graph Pattern Understanding for Zero-Shot VOS
The optical flow guidance strategy is ideal for obtaining motion information of objects in the video. It is widely utilized in video segmentation tasks. However, existing optical flow-based methods have a significant dep…
DecoderGraph Neural NetworkOptical Flow EstimationSemantic Segmentation+4General Object Foundation Model for Images and Videos at Scale
We present GLEE in this work, an object-level foundation model for locating and identifying objects in images and videos. Through a unified framework, GLEE accomplishes detection, segmentation, tracking, grounding, and i…
Instance SegmentationLong-tail Video Object SegmentationMulti-Object TrackingObject+8TAM-VT: Transformation-Aware Multi-scale Video Transformer for Segmentation and Tracking
Video Object Segmentation (VOS) has emerged as an increasingly important problem with availability of larger datasets and more complex and realistic settings, which involve long videos with global motion (e.g, in egocent…
Semantic SegmentationVideo Object SegmentationVideo Semantic Segmentation