Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
ActionVOS: Actions as Prompts for Video Object Segmentation
Delving into the realm of egocentric vision, the advancement of referring video object segmentation (RVOS) stands as pivotal in understanding human activities. However, existing RVOS task primarily relies on static attri…
ObjectReferring Video Object SegmentationSegmentationSemantic Segmentation+2Rethinking Image-to-Video Adaptation: An Object-centric Perspective
Image-to-video adaptation seeks to efficiently adapt image models for use in the video domain. Instead of finetuning the entire image backbone, many image-to-video adaptation paradigms use lightweight adapters for tempor…
Action RecognitionObjectObject DiscoverySemantic Segmentation+5Non-parametric Contextual Relationship Learning for Semantic Video Object Segmentation
We propose a novel approach for modeling semantic contextual relationships in videos. This graph-based model enables the learning and propagation of higher-level spatial-temporal contexts to facilitate the semantic label…
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationSubmodular video object proposal selection for semantic object segmentation
Learning a data-driven spatio-temporal semantic representation of the objects is the key to coherent and consistent labelling in video. This paper proposes to achieve semantic video object segmentation by learning a data…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1Context Propagation from Proposals for Semantic Video Object Segmentation
In this paper, we propose a novel approach to learning semantic contextual relationships in videos for semantic object segmentation. Our algorithm derives the semantic contexts from video object proposals which encode th…
ObjectSegmentationSemantic SegmentationSuperpixels+2Video Inpainting Localization with Contrastive Learning
Deep video inpainting is typically used as malicious manipulation to remove important objects for creating fake videos. It is significant to identify the inpainted regions blindly. This letter proposes a simple yet effec…
Contrastive LearningDecoderSemantic SegmentationVideo Inpainting+2PVUW 2024 Challenge on Complex Video Understanding: Methods and Results
Pixel-level Video Understanding in the Wild Challenge (PVUW) focus on complex video understanding. In this CVPR 2024 workshop, we add two new tracks, Complex Video Object Segmentation Track based on MOSE dataset and Moti…
SegmentationSemantic SegmentationvalidVideo Object Segmentation+32nd Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation
Motion Expression guided Video Segmentation is a challenging task that aims at segmenting objects in the video based on natural language expressions with motion descriptions. Unlike the previous referring video object se…
Instance SegmentationReferring Video Object SegmentationSegmentationSemantic Segmentation+4Trusted Video Inpainting Localization via Deep Attentive Noise Learning
Digital video inpainting techniques have been substantially improved with deep learning in recent years. Although inpainting is originally designed to repair damaged areas, it can also be used as malicious manipulation t…
Semantic SegmentationVideo InpaintingVideo Object SegmentationVideo Semantic SegmentationGroPrompt: Efficient Grounded Prompting and Adaptation for Referring Video Object Segmentation
Referring Video Object Segmentation (RVOS) aims to segment the object referred to by the query sentence throughout the entire video. Most existing methods require end-to-end training with dense mask annotations, which co…
Contrastive LearningObjectPositionPrompt Learning+6ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection
With the rapid development of depth sensor, more and more RGB-D videos could be obtained. Identifying the foreground in RGB-D videos is a fundamental and important task. However, the existing salient object detection (SO…
object-detectionObject DetectionSaliency DetectionSalient Object Detection+5RMem: Restricted Memory Banks Improve Video Object Segmentation
With recent video object segmentation (VOS) benchmarks evolving to challenging scenarios, we revisit a simple but overlooked strategy: restricting the size of memory banks. This diverges from the prevalent practice of ex…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic Segmentation2nd Place Solution for MOSE Track in CVPR 2024 PVUW workshop: Complex Video Object Segmentation
Complex video object segmentation serves as a fundamental task for a wide range of downstream applications such as video editing and automatic data annotation. Here we present the 2nd place solution in the MOSE track of …
Instance SegmentationSemantic SegmentationvalidVideo Editing+21st Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation
Motion Expression guided Video Segmentation (MeViS), as an emerging task, poses many new challenges to the field of referring video object segmentation (RVOS). In this technical report, we investigated and validated the …
Referring Video Object SegmentationSegmentationSemantic SegmentationVideo Object Segmentation+2Training-Free Robust Interactive Video Object Segmentation
Interactive video object segmentation is a crucial video task, having various applications from video editing to data annotating. However, current approaches struggle to accurately segment objects across diverse domains.…
Interactive Video Object SegmentationObjectPoint TrackingSegmentation+5A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation
Video object segmentation (VOS) -- predicting pixel-level regions for objects within each frame of a video -- is particularly challenging in agricultural scenarios, where videos of crops include hundreds of small, dense,…
Multi-Task LearningObjectOptical Flow EstimationSegmentation+33rd Place Solution for MeViS Track in CVPR 2024 PVUW workshop: Motion Expression guided Video Segmentation
Referring video object segmentation (RVOS) relies on natural language expressions to segment target objects in video, emphasizing modeling dense text-video relations. The current RVOS methods typically use independently …
Referring Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Segmentation+11st Place Solution for MOSE Track in CVPR 2024 PVUW Workshop: Complex Video Object Segmentation
Tracking and segmenting multiple objects in complex scenes has always been a challenge in the field of video object segmentation, especially in scenarios where objects are occluded and split into parts. In such cases, th…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+13rd Place Solution for MOSE Track in CVPR 2024 PVUW workshop: Complex Video Object Segmentation
Video Object Segmentation (VOS) is a vital task in computer vision, focusing on distinguishing foreground objects from the background across video frames. Our work draws inspiration from the Cutie model, and we investiga…
ObjectPositionSegmentationSemantic Segmentation+2Lifelong Learning Using a Dynamically Growing Tree of Sub-networks for Domain Generalization in Video Object Segmentation
Current state-of-the-art video object segmentation models have achieved great success using supervised learning with massive labeled training datasets. However, these models are trained using a single source domain and e…
Domain GeneralizationLifelong learningObjectSegmentation+3