Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
DTOS: Dynamic Time Object Sensing with Large Multimodal Model
Existing multimodal large language models (MLLMs) face significant challenges in Referring Video Object Segmentation(RVOS). We identify three critical challenges: (C1) insufficient quantitative representation of text…
Moment RetrievalReferring Video Object SegmentationRetrievalSemantic Segmentation+2Semantic and Sequential Alignment for Referring Video Object Segmentation
Referring video object segmentation (RVOS) seeks to segment the objects within a video referred by linguistic expressions. Existing RVOS solutions follow a "fuse then select" paradigm: establishing semantic correlati…
Instance SegmentationReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+1Decoupled Motion Expression Video Segmentation
Motion expression video segmentation aims to segment objects based on input motion descriptions. Compared with traditional referring video object segmentation, it focuses on motion and multi-object expressions and is…
Instance SegmentationReferring Video Object SegmentationSegmentationSemantic Segmentation+4M$^3$-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation
Intelligent robots need to interact with diverse objects across various environments. The appearance and state of objects frequently undergo complex transformations depending on the object properties, e.g., phase transit…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationStable Mean Teacher for Semi-supervised Video Action Detection
In this work, we focus on semi-supervised learning for video action detection. Video action detection requires spatiotemporal localization in addition to classification, and a limited amount of labels makes the model pro…
Action DetectionSemantic SegmentationSemi_supervised Video Action DetectionSemi-Supervised Video Action Detection+3Video Decomposition Prior: A Methodology to Decompose Videos into Layers
In the evolving landscape of video enhancement and editing methodologies, a majority of deep learning techniques often rely on extensive datasets of observed input and ground truth sequence pairs for optimal performance.…
Semantic SegmentationVideo EditingVideo EnhancementVideo Object Segmentation+1Multi-Granularity Video Object Segmentation
Current benchmarks for video segmentation are limited to annotating only salient objects (i.e., foreground instances). Despite their impressive architectural designs, previous works trained on these benchmarks have strug…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Referring Video Object Segmentation via Language-aligned Track Selection
Referring video object segmentation (RVOS) requires tracking and segmenting an object throughout a video according to a given natural language expression, demanding both complex motion understanding and the alignment of …
ObjectObject TrackingReferring Video Object SegmentationSemantic Segmentation+3Track Anything Behind Everything: Zero-Shot Amodal Video Object Segmentation
We present Track Anything Behind Everything (TABE), a novel dataset, pipeline, and evaluation framework for zero-shot amodal completion from visible masks. Unlike existing methods that require pretrained class labels, ou…
3D ReconstructionSegmentationSemantic SegmentationVideo Object Segmentation+1Efficient Track Anything
Segment Anything Model 2 (SAM 2) has emerged as a powerful tool for video object segmentation and tracking anything. Key components of SAM 2 that drive the impressive video object segmentation performance include a large…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation
Referring Video Object Segmentation (RVOS) relies on natural language expressions to segment an object in a video clip. Existing methods restrict reasoning either to independent short clips, losing global context, or pro…
Natural Language UnderstandingReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+2HyperSeg: Towards Universal Visual Segmentation with Large Language Model
This paper aims to address universal segmentation for image and video perception with the strong reasoning ability empowered by Visual Large Language Models (VLLMs). Despite significant progress in current unified segmen…
Language ModelingLarge Language ModelOpen Vocabulary Semantic SegmentationPanoptic Segmentation+9ClickTrack: Towards Real-time Interactive Single Object Tracking
Single object tracking(SOT) relies on precise object bounding box initialization. In this paper, we reconsidered the deficiencies in the current approaches to initializing single object trackers and propose a new paradig…
ObjectObject TrackingSemantic SegmentationVideo Object Segmentation+1IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
Shape assembly is a ubiquitous task in daily life, integral for constructing complex 3D structures like IKEA furniture. While significant progress has been made in developing autonomous agents for shape assembly, existin…
Pose EstimationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationLiVOS: Light Video Object Segmentation with Gated Linear Matching
Semi-supervised video object segmentation (VOS) has been largely driven by space-time memory (STM) networks, which store past frame features in a spatiotemporal memory to segment the current frame via softmax attention. …
GPUSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Continuous Spatio-Temporal Memory Networks for 4D Cardiac Cine MRI Segmentation
Current cardiac cine magnetic resonance image (cMR) studies focus on the end diastole (ED) and end systole (ES) phases, while ignoring the abundant temporal information in the whole image sequence. This is because whole …
AnatomyMRI segmentationSegmentationSemantic Segmentation+2Addressing Issues with Working Memory in Video Object Segmentation
Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the inter…
Inductive BiasObjectSemantic SegmentationVideo Object Segmentation+1SMITE: Segment Me In TimE
Segmenting an object in a video presents significant challenges. Each pixel must be accurately labelled, and these labels must remain consistent across frames. The difficulty increases when the segmentation is with arbit…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Segmentation+1SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
The Segment Anything Model 2 (SAM 2) has emerged as a powerful foundation model for object segmentation in both images and videos, paving the way for various downstream video applications. The crucial design of SAM 2 for…
Heuristic SearchObjectSegmentationSemantic Segmentation+4One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos
We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. Leveraging the reasoning capabilities and world knowledge of l…
AllImage SegmentationLanguage ModelingLanguage Modelling+11