Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
One-shot Training for Video Object Segmentation
Video Object Segmentation (VOS) aims to track objects across frames in a video and segment them based on the initial annotated frame of the target objects. Previous VOS works typically rely on fully annotated videos for …
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationHarnessing Vision-Language Pretrained Models with Temporal-Aware Adaptation for Referring Video Object Segmentation
The crux of Referring Video Object Segmentation (RVOS) lies in modeling dense text-video relations to associate abstract linguistic concepts with dynamic visual contents at pixel-level. Current RVOS methods typically use…
Referring Expression SegmentationReferring Video Object SegmentationRelationSemantic Segmentation+2Global Motion Understanding in Large-Scale Video Object Segmentation
In this paper, we show that transferring knowledge from other domains of video understanding combined with large-scale learning can improve robustness of Video Object Segmentation (VOS) under complex circumstances. Namel…
Instance SegmentationOptical Flow EstimationSegmentationSemantic Segmentation+4DeVOS: Flow-Guided Deformable Transformer for Video Object Segmentation
The recent works on Video Object Segmentation achieved remarkable results by matching dense semantic and instance-level features between the current and previous frames for long-time propagation. Nevertheless, global fea…
Optical Flow EstimationSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationSpace-time Reinforcement Network for Video Object Segmentation
Recently, video object segmentation (VOS) networks typically use memory-based methods: for each query frame, the mask is predicted by space-time matching to memory frames. Despite these methods having superior performanc…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationLVOS: A Benchmark for Large-scale Long-term Video Object Segmentation
Video object segmentation (VOS) aims to distinguish and track target objects in a video. Despite the excellent performance achieved by off-the-shell VOS models, existing VOS benchmarks mainly focus on short-term videos l…
AttributeSemantic SegmentationVideo Object SegmentationVideo Semantic Segmentation360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos
Visual object tracking and segmentation in omnidirectional videos are challenging due to the wide field-of-view and large spherical distortion brought by 360{\deg} images. To alleviate these problems, we introduce a nove…
ObjectObject TrackingSegmentationSemantic Segmentation+3Dynamic in Static: Hybrid Visual Correspondence for Self-Supervised Video Object Segmentation
Conventional video object segmentation (VOS) methods usually necessitate a substantial volume of pixel-level annotated video data for fully supervised learning. In this paper, we present HVC, a \textbf{h}ybrid static-dyn…
Semantic SegmentationVideo Object SegmentationVideo Semantic SegmentationMoving Object Segmentation: All You Need Is SAM (and Flow)
The objective of this paper is motion segmentation -- discovering and segmenting the moving objects in a video. This is a much studied area with numerous careful, and sometimes complex, approaches and training schemes in…
AllMotion SegmentationObjectOptical Flow Estimation+5Spatial-Temporal Multi-level Association for Video Object Segmentation
Existing semi-supervised video object segmentation methods either focus on temporal feature matching or spatial-temporal feature modeling. However, they do not address the issues of sufficient target interaction and effi…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Event-assisted Low-Light Video Object Segmentation
In the realm of video object segmentation (VOS), the challenge of operating under low-light conditions persists, resulting in notably degraded image quality and compromised accuracy when comparing query and memory frames…
ObjectSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationTemporally Consistent Referring Video Object Segmentation with Hybrid Memory
Referring Video Object Segmentation (R-VOS) methods face challenges in maintaining consistent object segmentation due to temporal context variability and the presence of other visually similar objects. We propose an end-…
HTRObjectReferring Expression SegmentationReferring Video Object Segmentation+5Annolid: Annotate, Segment, and Track Anything You Need
Annolid is a deep learning-based software package designed for the segmentation, labeling, and tracking of research targets within video files, focusing primarily on animal behavior analysis. Based on state-of-the-art in…
Instance SegmentationSegmentationSemantic SegmentationVideo Object Segmentation+1Efficient Video Object Segmentation via Modulated Cross-Attention Memory
Recently, transformer-based approaches have shown promising results for semi-supervised video object segmentation. However, these approaches typically struggle on long videos due to increased GPU memory demands, as they …
GPUObjectSegmentationSemantic Segmentation+3PSALM: Pixelwise SegmentAtion with Large Multi-Modal Model
PSALM is a powerful extension of the Large Multi-modal Model (LMM) to address the segmentation task challenges. To overcome the limitation of the LMM being limited to textual output, PSALM incorporates a mask decoder and…
DecoderGeneralized Referring Expression SegmentationImage SegmentationPanoptic Segmentation+6Video Object Segmentation with Dynamic Query Modulation
Storing intermediate frame segmentations as memory for long-range context modeling, spatial-temporal memory-based methods have recently showcased impressive results in semi-supervised video object segmentation (SVOS). Ho…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation
In this paper, we explore the visual representations produced from a pre-trained text-to-video (T2V) diffusion model for video understanding tasks. We hypothesize that the latent representation learned from a pretrained …
Referring Video Object SegmentationSemantic SegmentationVideo Object SegmentationVideo Semantic Segmentation+1OneVOS: Unifying Video Object Segmentation with All-in-One Transformer Framework
Contemporary Video Object Segmentation (VOS) approaches typically consist stages of feature extraction, matching, memory management, and multiple objects aggregation. Recent advanced models either employ a discrete model…
AllManagementSemantic SegmentationVideo Object Segmentation+1Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment Anything
The Segment Anything Model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each frame and large computational cost limit…
GPUPoint TrackingSegmentationSemantic Segmentation+4ClickVOS: Click Video Object Segmentation
Video Object Segmentation (VOS) task aims to segment objects in videos. However, previous settings either require time-consuming manual masks of target objects at the first frame during inference or lack the flexibility …
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+1