Papers Referring Video Object Segmentation
“Referring Video Object Segmentation” 태그가 달린 논문 106편 · 필터 해제
LTCA: Long-range Temporal Context Attention for Referring Video Object Segmentation
Referring Video Segmentation (RVOS) aims to segment objects in videos given linguistic expressions. The key to solving RVOS is to extract long-range temporal context information from the interactions of expressions and v…
Referring Video Object SegmentationVideo SegmentationTemporal Prompting Matters: Rethinking Referring Video Object Segmentation
Referring Video Object Segmentation (RVOS) aims to segment the object referred to by the query sentence in the video. Most existing methods require end-to-end training with dense mask annotations, which could be computat…
Referring Video Object SegmentationDeforming Videos to Masks: Flow Matching for Referring Video Segmentation
Referring Video Object Segmentation (RVOS) requires segmenting specific objects in a video guided by a natural language description. The core challenge of RVOS is to anchor abstract linguistic concepts onto a specific se…
Referring Video Object SegmentationVideo SegmentationSVAC: Scaling Is All You Need For Referring Video Object Segmentation
Referring Video Object Segmentation (RVOS) aims to segment target objects in video sequences based on natural language descriptions. While recent advances in Multi-modal Large Language Models (MLLMs) have improved RVOS p…
Referring Video Object SegmentationSa2VA-i: Improving Sa2VA Results with Consistent Training and Inference
Sa2VA is a recent model for language-guided dense grounding in images and video that achieves state-of-the-art results on multiple segmentation benchmarks and that has become widely popular. However, we found that Sa2VA …
Referring Video Object SegmentationVideo SegmentationThe 1st Solution for 7th LSVOS RVOS Track: SaSaSa2VA
Referring video object segmentation (RVOS) requires segmenting and tracking objects in videos conditioned on natural-language expressions, demanding fine-grained understanding of both appearance and motion. Building on S…
Referring Video Object SegmentationVideo SegmentationMitigating Query Selection Bias in Referring Video Object Segmentation
Recently, query-based methods have achieved remarkable performance in Referring Video Object Segmentation (RVOS) by using textual static object queries to drive cross-modal alignment. However, these static queries are ea…
Referring Video Object SegmentationUnleashing Hierarchical Reasoning: An LLM-Driven Framework for Training-Free Referring Video Object Segmentation
Referring Video Object Segmentation (RVOS) aims to segment an object of interest throughout a video based on a language description. The prominent challenge lies in aligning static text with dynamic visual content, parti…
Referring Video Object SegmentationTemporal-Conditional Referring Video Object Segmentation with Noise-Free Text-to-Video Diffusion Model
Referring Video Object Segmentation (RVOS) aims to segment specific objects in a video according to textual descriptions. We observe that recent RVOS approaches often place excessive emphasis on feature extraction and te…
Referring Video Object SegmentationTemporal Grounding as a Learning Signal for Referring Video Object Segmentation
Referring Video Object Segmentation (RVOS) aims to segment and track objects in videos based on natural language expressions, requiring precise alignment between visual content and textual queries. However, existing meth…
Referring Video Object SegmentationEventRR: Event Referential Reasoning for Referring Video Object Segmentation
Referring Video Object Segmentation (RVOS) aims to segment out the object in a video referred by an expression. Current RVOS methods view referring expressions as unstructured sequences, neglecting their crucial semantic…
Referring Video Object SegmentationReferring ExpressionPlanner-Refiner: Dynamic Space-Time Refinement for Vision-Language Alignment in Videos
Vision-language alignment in video must address the complexity of language, evolving interacting entities, their action chains, and semantic gaps between language and vision. This work introduces Planner-Refiner, a frame…
Referring Video Object SegmentationVideoMolmo: Spatio-Temporal Grounding Meets Pointing
Spatio-temporal localization is vital for precise interactions across diverse domains, from biological research to autonomous navigation and interactive interfaces. Current video-based approaches, while proficient in tra…
Autonomous DrivingAutonomous NavigationCell TrackingReferring Video Object Segmentation+4InterRVOS: Interaction-aware Referring Video Object Segmentation
Referring video object segmentation aims to segment the object in a video corresponding to a given natural language expression. While prior works have explored various referring scenarios, including motion-centric or mul…
8kObjectReferring Video Object SegmentationSemantic Segmentation+3Long-RVOS: A Comprehensive Benchmark for Long-term Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to identify, track and segment the objects in a video based on language descriptions, which has received great attention in recent years. However, existing datasets remain …
Referring Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationFew-Shot Referring Video Single- and Multi-Object Segmentation via Cross-Modal Affinity with Instance Sequence Matching
Referring video object segmentation (RVOS) aims to segment objects in videos guided by natural language descriptions. We propose FS-RVOS, a Transformer-based model with two key components: a cross-modal affinity module a…
ObjectReferring Video Object SegmentationSegmentationSemantic Segmentation+2GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
This paper proposes a novel framework utilizing multi-modal large language models (MLLMs) for referring video object segmentation (RefVOS). Previous MLLM-based methods commonly struggle with the dilemma between "Ref" and…
Contrastive LearningLanguage ModelingLanguage ModellingLarge Language Model+6The 1st Solution for 4th PVUW MeViS Challenge: Unleashing the Potential of Large Multimodal Models for Referring Video Segmentation
Motion expression video segmentation is designed to segment objects in accordance with the input motion expressions. In contrast to the conventional Referring Video Object Segmentation (RVOS), it places emphasis on motio…
Inference OptimizationReferring Video Object SegmentationSegmentationSemantic Segmentation+34th PVUW MeViS 3rd Place Report: Sa2VA
Referring video object segmentation (RVOS) is a challenging task that requires the model to segment the object in a video given the language description. MeViS is a recently proposed dataset that contains motion expressi…
Language ModelingLanguage ModellingLarge Language ModelReferring Expression+4ReferDINO-Plus: 2nd Solution for 4th PVUW MeViS Challenge at CVPR 2025
Referring Video Object Segmentation (RVOS) aims to segment target objects throughout a video based on a text description. This task has attracted increasing attention in the field of computer vision due to its promising …
ObjectReferring Video Object SegmentationSemantic SegmentationVideo Editing+2