Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation
Few-Shot Video Object Segmentation (FSVOS) aims to segment objects in a query video with the same category defined by a few annotated support images. However, this task was seldom explored. In this work, based on IPMT, a…
Image SegmentationSegmentationSemantic SegmentationVideo Object Segmentation+1Tracking Anything with Decoupled Video Segmentation
Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary settings. To 'track anything' without train…
Open-Vocabulary Video SegmentationOpen-World Video SegmentationPanoptic SegmentationReferring Expression Segmentation+9Temporal Collection and Distribution for Referring Video Object Segmentation
Referring video object segmentation aims to segment a referent throughout a video sequence according to a natural language expression. It requires aligning the natural language expression with the objects' motions and th…
ObjectReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+1Robust Visual Tracking by Motion Analyzing
In recent years, Video Object Segmentation (VOS) has emerged as a complementary method to Video Object Tracking (VOT). VOS focuses on classifying all the pixels around the target, allowing for precise shape labeling, whi…
Object TrackingSegmentationSemantic SegmentationTensor Decomposition+4Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples
Referring video object segmentation (RVOS), as a supervised learning task, relies on sufficient annotated data for a given scene. However, in more realistic scenarios, only minimal annotations are available for a new sce…
Referring Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationJoint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation
Current prevailing Video Object Segmentation (VOS) methods usually perform dense matching between the current and reference frames after extracting their features. One on hand, the decoupled modeling restricts the target…
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationIntegrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation
Tracking any given object(s) spatially and temporally is a common purpose in Visual Object Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation have been attempted in some studies but they …
ObjectObject TrackingRepresentation LearningSegmentation+5LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-training
Learning object segmentation in image and video datasets without human supervision is a challenging problem. Humans easily identify moving salient objects in videos using the gestalt principle of common fate, which sugge…
ObjectObject DiscoverySaliency DetectionSegmentation+3Scalable Video Object Segmentation with Simplified Framework
The current popular methods for video object segmentation (VOS) implement feature matching through several hand-crafted modules that separately perform feature extraction and matching. However, the above hand-crafted des…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationMeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
This paper strives for motion expressions guided video segmentation, which focuses on segmenting objects in video content based on a sentence describing the motion of the objects. Existing referring video object datasets…
Motion Expressions Guided Video SegmentationObjectReferring Video Object SegmentationSegmentation+5Isomer: Isomerous Transformer for Zero-shot Video Object Segmentation
Recent leading zero-shot video object segmentation (ZVOS) works devote to integrating appearance and motion information by elaborately designing feature fusion modules and identically applying them in multiple feature st…
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationZero-Shot Video Object SegmentationExpression Prompt Collaboration Transformer for Universal Referring Video Object Segmentation
Audio-guided Video Object Segmentation (A-VOS) and Referring Video Object Segmentation (R-VOS) are two highly related tasks that both aim to segment specific objects from video sequences according to expression prompts. …
Contrastive LearningObjectReferring Expression SegmentationReferring Video Object Segmentation+4Learning Referring Video Object Segmentation from Weak Annotation
Referring video object segmentation (RVOS) is a task that aims to segment the target object in all video frames based on a sentence describing the object. Although existing RVOS methods have achieved significant performa…
Contrastive LearningObjectReferring Video Object SegmentationSegmentation+4XMem++: Production-level Video Segmentation From Few Annotated Frames
Despite advancements in user-guided video segmentation, extracting complex objects consistently for highly complex scenes is still a labor-intensive task, especially for production. It is not uncommon that a majority of …
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+2Tracking Anything in High Quality
Visual object tracking is a fundamental video task in computer vision. Recently, the notably increasing power of perception algorithms allows the unification of single/multiobject and box/mask-based tracking. Among them,…
ObjectObject TrackingSemantic SegmentationSemi-Supervised Video Object Segmentation+3Spectrum-guided Multi-granularity Referring Video Object Segmentation
Current referring video object segmentation (R-VOS) techniques extract conditional kernels from encoded (low-resolution) vision-language features to segment the decoded high-resolution features. We discovered that this c…
ObjectReferring Expression SegmentationReferring Video Object SegmentationSegmentation+3OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims at segmenting an object in a video following human instruction. Current state-of-the-art methods fall into an offline pattern, in which each clip independently interacts wi…
Referring Expression SegmentationReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+1Hierarchical Spatiotemporal Transformers for Video Object Segmentation
This paper presents a novel framework called HST for semi-supervised video object segmentation (VOS). HST extracts image and video features using the latest Swin Transformer and Video Swin Transformer to inherit their in…
Inductive BiasObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2Holistic Prototype Attention Network for Few-Shot VOS
Few-shot video object segmentation (FSVOS) aims to segment dynamic objects of unseen classes by resorting to a small set of support images that contain pixel-level object annotations. Existing methods have demonstrated t…
Graph AttentionSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationMultiscale Memory Comparator Transformer for Few-Shot Video Segmentation
Few-shot video segmentation is the task of delineating a specific novel class in a query video using few labelled support images. Typical approaches compare support and query features while limiting comparisons to a sing…
DecoderSegmentationSemantic SegmentationVideo Object Segmentation+2