Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Saliency-Motion Guided Trunk-Collateral Network for Unsupervised Video Object Segmentation
Recent mainstream unsupervised video object segmentation (UVOS) motion-appearance approaches use either the bi-encoder structure to separately encode motion and appearance features, or the uni-encoder structure for joint…
Optical Flow EstimationSalient Object DetectionSemantic SegmentationUnsupervised Video Object Segmentation+3The 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+4Zero-Shot 4D Lidar Panoptic Segmentation
Zero-shot 4D segmentation and recognition of arbitrary objects in Lidar is crucial for embodied navigation, with applications ranging from streaming perception to semantic mapping and localization. However, the primary c…
DiversityPanoptic SegmentationPseudo LabelScene Understanding+4CamoSAM2: Motion-Appearance Induced Auto-Refining Prompts for Video Camouflaged Object Detection
The Segment Anything Model 2 (SAM2), a prompt-guided video foundation model, has remarkably performed in video object segmentation, drawing significant attention in the community. Due to the high similarity between camou…
Camouflaged Object Segmentationobject-detectionObject DetectionSemantic Segmentation+2ReferDINO-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+2One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks
Video object segmentation is crucial for the efficient analysis of complex medical video data, yet it faces significant challenges in data availability and annotation. We introduce the task of one-shot medical video obje…
DecoderSegmentationSemantic SegmentationVideo Object Segmentation+1Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning
Few-shot video object segmentation aims to reduce annotation costs; however, existing methods still require abundant dense frame annotations for training, which are scarce in the medical domain. We investigate an extreme…
SegmentationSemantic SegmentationVideo Object SegmentationVideo Segmentation+1AUTV: Creating Underwater Video Datasets with Pixel-wise Annotations
Underwater video analysis, hampered by the dynamic marine environment and camera motion, remains a challenging task in computer vision. Existing training-free video generation techniques, learning motion dynamics on the …
Semantic SegmentationVideo GenerationVideo InpaintingVideo Object Segmentation+1Leveraging Motion Information for Better Self-Supervised Video Correspondence Learning
Self-supervised video correspondence learning depends on the ability to accurately associate pixels between video frames that correspond to the same visual object. However, achieving reliable pixel matching without super…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationInvestigation of Frame Differences as Motion Cues for Video Object Segmentation
Automatic Video Object Segmentation (AVOS) refers to the task of autonomously segmenting target objects in video sequences without relying on human-provided annotations in the first frames. In AVOS, the use of motion inf…
Optical Flow EstimationSegmentationSemantic SegmentationVideo Object Segmentation+1Find First, Track Next: Decoupling Identification and Propagation in Referring Video Object Segmentation
Referring video object segmentation aims to segment and track a target object in a video using a natural language prompt. Existing methods typically fuse visual and textual features in a highly entangled manner, processi…
ObjectReferring Video Object SegmentationSegmentationSemantic Segmentation+2An Analysis of Data Transformation Effects on Segment Anything 2
Video object segmentation (VOS) is a critical task in the development of video perception and understanding. The Segment-Anything Model 2 (SAM 2), released by Meta AI, is the current state-of-the-art architecture for end…
Semantic SegmentationVideo Object SegmentationVideo SegmentationVideo Semantic Segmentation+1Wandering around: A bioinspired approach to visual attention through object motion sensitivity
Active vision enables dynamic visual perception, offering an alternative to static feedforward architectures in computer vision, which rely on large datasets and high computational resources. Biological selective attenti…
Low-latency processingMotion SegmentationSegmentationSemantic Segmentation+4HD-EPIC: A Highly-Detailed Egocentric Video Dataset
We present a validation dataset of newly-collected kitchen-based egocentric videos, manually annotated with highly detailed and interconnected ground-truth labels covering: recipe steps, fine-grained actions, ingredients…
Action RecognitionNutritionObjectSemantic Segmentation+3ReferDINO: Referring Video Object Segmentation with Visual Grounding Foundations
Referring video object segmentation (RVOS) aims to segment target objects throughout a video based on a text description. Despite notable progress in recent years, current RVOS models remain struggle to handle complicate…
DecoderObjectReferring Expression SegmentationReferring Video Object Segmentation+4MPG-SAM 2: Adapting SAM 2 with Mask Priors and Global Context for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to segment objects in a video according to textual descriptions, which requires the integration of multimodal information and temporal dynamics perception. The Segment Anyt…
Referring Expression SegmentationReferring Video Object SegmentationSemantic SegmentationVideo Object Segmentation+2Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation
In this paper, we address the challenges in unsupervised video object segmentation (UVOS) by proposing an efficient algorithm, termed MTNet, which concurrently exploits motion and temporal cues. Unlike previous methods t…
Objectobject-detectionObject DetectionSalient Object Detection+6Multi-Context Temporal Consistent Modeling for Referring Video Object Segmentation
Referring video object segmentation aims to segment objects within a video corresponding to a given text description. Existing transformer-based temporal modeling approaches face challenges related to query inconsistency…
Referring Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationSa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
This work presents Sa2VA, the first unified model for dense grounded understanding of both images and videos. Unlike existing multi-modal large language models, which are often limited to specific modalities and tasks, S…
2kLanguage ModelingLanguage ModellingObject+6