Papers Video Object Segmentation
“Video Object Segmentation” 태그가 달린 논문 608편 · 필터 해제
Efficient Unsupervised Video Object Segmentation Network Based on Motion Guidance
Due to the problem of performance constraints of unsupervised video object detection, its large-scale application is limited. In response to this pain point, we propose another excellent method to solve this problematic …
object-detectionObject DetectionOptical Flow EstimationSemantic Segmentation+4Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks
There is limited understanding of the information captured by deep spatiotemporal models in their intermediate representations. For example, while evidence suggests that action recognition algorithms are heavily influenc…
Action RecognitionInstance SegmentationSemantic SegmentationVideo Instance Segmentation+2Two-Level Temporal Relation Model for Online Video Instance Segmentation
In Video Instance Segmentation (VIS), current approaches either focus on the quality of the results, by taking the whole video as input and processing it offline; or on speed, by handling it frame by frame at the cost of…
Graph Neural NetworkInstance SegmentationRelationSegmentation+5VLT: Vision-Language Transformer and Query Generation for Referring Segmentation
We propose a Vision-Language Transformer (VLT) framework for referring segmentation to facilitate deep interactions among multi-modal information and enhance the holistic understanding to vision-language features. There …
Referring Expression SegmentationReferring Video Object SegmentationVideo Object SegmentationSelf-supervised Amodal Video Object Segmentation
Amodal perception requires inferring the full shape of an object that is partially occluded. This task is particularly challenging on two levels: (1) it requires more information than what is contained in the instant ret…
ObjectSegmentationSelf-Supervised LearningSemantic Segmentation+4Decoupling 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+1Global Spectral Filter Memory Network for Video Object Segmentation
This paper studies semi-supervised video object segmentation through boosting intra-frame interaction. Recent memory network-based methods focus on exploiting inter-frame temporal reference while paying little attention …
AttributeDecoderObjectSegmentation+4Self-supervised Video Representation Learning with Motion-Aware Masked Autoencoders
Masked autoencoders (MAEs) have emerged recently as art self-supervised spatiotemporal representation learners. Inheriting from the image counterparts, however, existing video MAEs still focus largely on static appearanc…
Representation LearningSemantic SegmentationVideo Object SegmentationVideo Semantic SegmentationEPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
We introduce VISOR, a new dataset of pixel annotations and a benchmark suite for segmenting hands and active objects in egocentric video. VISOR annotates videos from EPIC-KITCHENS, which comes with a new set of challenge…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video
Multiple existing benchmarks involve tracking and segmenting objects in video e.g., Video Object Segmentation (VOS) and Multi-Object Tracking and Segmentation (MOTS), but there is little interaction between them due to t…
Long-tail Video Object SegmentationMulti-Object TrackingMulti-Object Tracking and SegmentationObject+6A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation
We propose a simple, yet powerful approach for unsupervised object segmentation in videos. We introduce an objective function whose minimum represents the mask of the main salient object over the input sequence. It only …
Clusteringglobal-optimizationObjectSemantic Segmentation+5Unsupervised Video Object Segmentation via Prototype Memory Network
Unsupervised video object segmentation aims to segment a target object in the video without a ground truth mask in the initial frame. This challenging task requires extracting features for the most salient common objects…
ObjectOptical Flow EstimationSelf-LearningSemantic Segmentation+3Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
Unsupervised video object segmentation (VOS) aims to detect the most salient object in a video sequence at the pixel level. In unsupervised VOS, most state-of-the-art methods leverage motion cues obtained from optical fl…
Optical Flow EstimationSemantic SegmentationUnsupervised Video Object SegmentationVideo Object Segmentation+1Pixel-Level Equalized Matching for Video Object Segmentation
Feature similarity matching, which transfers the information of the reference frame to the query frame, is a key component in semi-supervised video object segmentation. If surjective matching is adopted, background distr…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
In this paper, we describe a graph-based algorithm that uses the features obtained by a self-supervised transformer to detect and segment salient objects in images and videos. With this approach, the image patches that c…
Object DiscoverySaliency DetectionSegmentationSemantic Segmentation+6SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
Matching-based methods, especially those based on space-time memory, are significantly ahead of other solutions in semi-supervised video object segmentation (VOS). However, continuously growing and redundant template fea…
Semantic SegmentationSemi-Supervised Video Object SegmentationVideo Object SegmentationVideo Semantic SegmentationTwo-Stream Networks for Object Segmentation in Videos
Existing matching-based approaches perform video object segmentation (VOS) via retrieving support features from a pixel-level memory, while some pixels may suffer from lack of correspondence in the memory (i.e., unseen),…
ObjectRetrievalSegmentationSemantic Segmentation+3Per-Clip Video Object Segmentation
Recently, memory-based approaches show promising results on semi-supervised video object segmentation. These methods predict object masks frame-by-frame with the help of frequently updated memory of the previous mask. Di…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation
Video Object Segmentation (VOS) is fundamental to video understanding. Transformer-based methods show significant performance improvement on semi-supervised VOS. However, existing work faces challenges segmenting visuall…
ObjectOptical Flow EstimationSegmentationSemantic Segmentation+5Multi-Attention Network for Compressed Video Referring Object Segmentation
Referring video object segmentation aims to segment the object referred by a given language expression. Existing works typically require compressed video bitstream to be decoded to RGB frames before being segmented, whic…
ObjectReferring Expression SegmentationReferring Video Object SegmentationSegmentation+3