Papers Semi-Supervised Video Object Segmentation
“Semi-Supervised Video Object Segmentation” 태그가 달린 논문 154편 · 필터 해제
SpVOS: Efficient Video Object Segmentation with Triple Sparse Convolution
Semi-supervised video object segmentation (Semi-VOS), which requires only annotating the first frame of a video to segment future frames, has received increased attention recently. Among existing pipelines, the memory-ma…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Putting the Object Back into Video Object Segmentation
We present Cutie, a video object segmentation (VOS) network with object-level memory reading, which puts the object representation from memory back into the video object segmentation result. Recent works on VOS employ bo…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+3Sub-token ViT Embedding via Stochastic Resonance Transformers
Vision Transformer (ViT) architectures represent images as collections of high-dimensional vectorized tokens, each corresponding to a rectangular non-overlapping patch. This representation trades spatial granularity for …
Depth EstimationDepth PredictionImage RetrievalObject Discovery+5Memory-Efficient Continual Learning Object Segmentation for Long Video
Recent state-of-the-art semi-supervised Video Object Segmentation (VOS) methods have shown significant improvements in target object segmentation accuracy when information from preceding frames is used in segmenting the …
Continual LearningObjectSegmentationSemantic Segmentation+3Tracking 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+9XMem++: 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+3Hierarchical 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+2ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: Semi-Supervised Video Object Segmentation
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object segmentation. In this study, we introduce MSDeAOT, a variant of the AO…
ObjectPositionSegmentationSemantic Segmentation+3TrickVOS: A Bag of Tricks for Video Object Segmentation
Space-time memory (STM) network methods have been dominant in semi-supervised video object segmentation (SVOS) due to their remarkable performance. In this work, we identify three key aspects where we can improve such me…
DecoderObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2READMem: Robust Embedding Association for a Diverse Memory in Unconstrained Video Object Segmentation
We present READMem (Robust Embedding Association for a Diverse Memory), a modular framework for semi-automatic video object segmentation (sVOS) methods designed to handle unconstrained videos. Contemporary sVOS works typ…
Semantic SegmentationSemi-Supervised Video Object SegmentationVideo Object SegmentationVideo Semantic SegmentationVideo Object Segmentation in Panoptic Wild Scenes
In this paper, we introduce semi-supervised video object segmentation (VOS) to panoptic wild scenes and present a large-scale benchmark as well as a baseline method for it. Previous benchmarks for VOS with sparse annotat…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Robust and Efficient Memory Network for Video Object Segmentation
This paper proposes a Robust and Efficient Memory Network, referred to as REMN, for studying semi-supervised video object segmentation (VOS). Memory-based methods have recently achieved outstanding VOS performance by per…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1CLVOS23: A Long Video Object Segmentation Dataset for Continual Learning
Continual learning in real-world scenarios is a major challenge. A general continual learning model should have a constant memory size and no predefined task boundaries, as is the case in semi-supervised Video Object Seg…
Continual LearningSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation
This paper tackles the problem of semi-supervised video object segmentation on resource-constrained devices, such as mobile phones. We formulate this problem as a distillation task, whereby we demonstrate that small spac…
Contrastive LearningKnowledge DistillationRepresentation LearningSemantic Segmentation+3Flow-guided Semi-supervised Video Object Segmentation
We propose an optical flow-guided approach for semi-supervised video object segmentation. Optical flow is usually exploited as additional guidance information in unsupervised video object segmentation. However, its relev…
DecoderObjectOptical Flow EstimationSegmentation+5Alignment Before Aggregation: Trajectory Memory Retrieval Network for Video Object Segmentation
Memory-based methods in semi-supervised video object segmentation task achieve competitive performance by performing dense matching between query and memory frames. However, most of the existing methods neglect the f…
RetrievalSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Look Before You Match: Instance Understanding Matters in Video Object Segmentation
Exploring dense matching between the current frame and past frames for long-range context modeling, memory-based methods have demonstrated impressive results in video object segmentation (VOS) recently. Nevertheless, due…
Instance SegmentationSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Learning to Learn Better for Video Object Segmentation
Recently, the joint learning framework (JOINT) integrates matching based transductive reasoning and online inductive learning to achieve accurate and robust semi-supervised video object segmentation (SVOS). However, usin…
Inductive LearningObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2Decoupling Features in Hierarchical Propagation for Video Object Segmentation
This paper focuses on developing a more effective method of hierarchical propagation for semi-supervised Video Object Segmentation (VOS). Based on vision transformers, the recently-developed Associating Objects with Tran…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1