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One-Shot Video Object Segmentation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-10593-2_43openalex-snapshot
Supervoxel-Consistent Foreground Propagation in Video
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_35openalex-snapshot
Convolutional Oriented Boundaries
inferredcites →https://doi.org/10.1007/978-3-319-46466-4_32openalex-snapshot
Instance-Sensitive Fully Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-46487-9_38openalex-snapshot
The Fast Bilateral Solver
inferredcites →https://doi.org/10.1007/978-3-642-15555-0_21openalex-snapshot
Object Segmentation by Long Term Analysis of Point Trajectories
inferredcites →https://doi.org/10.1007/978-3-642-33715-4_36openalex-snapshot
Active Frame Selection for Label Propagation in Videos
inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1007/s11263-017-1004-zopenalex-snapshot
Holistically-Nested Edge Detection
inferredcites →https://doi.org/10.1016/j.cviu.2012.11.005openalex-snapshot
Hough-based tracking of non-rigid objects
inferredcites →https://doi.org/10.1109/cvpr.2010.5539893openalex-snapshot
Efficient hierarchical graph-based video segmentation
inferredcites →https://doi.org/10.1109/cvpr.2012.6247883openalex-snapshot
Video segmentation by tracing discontinuities in a trajectory embedding
inferredcites →https://doi.org/10.1109/cvpr.2012.6248065openalex-snapshot
Learning object class detectors from weakly annotated video
inferredcites →https://doi.org/10.1109/cvpr.2013.267openalex-snapshot
A Video Representation Using Temporal Superpixels
inferredcites →https://doi.org/10.1109/cvpr.2014.119openalex-snapshot
The Role of Context for Object Detection and Semantic Segmentation in the Wild
inferredcites →https://doi.org/10.1109/cvpr.2014.55openalex-snapshot
SeamSeg: Video Object Segmentation Using Patch Seams
inferredcites →https://doi.org/10.1109/cvpr.2014.81openalex-snapshot
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298642openalex-snapshot
Hypercolumns for object segmentation and fine-grained localization
inferredcites →https://doi.org/10.1109/cvpr.2015.7298835openalex-snapshot
JOTS: Joint Online Tracking and Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298961openalex-snapshot
Saliency-aware geodesic video object segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7299055openalex-snapshot
Causal video object segmentation from persistence of occlusions
inferredcites →https://doi.org/10.1109/cvpr.2016.28openalex-snapshot
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
inferredcites →https://doi.org/10.1109/cvpr.2016.392openalex-snapshot
Semantic Segmentation with Boundary Neural Fields
inferredcites →https://doi.org/10.1109/cvpr.2016.423openalex-snapshot
Video Segmentation via Object Flow
inferredcites →https://doi.org/10.1109/cvpr.2016.465openalex-snapshot
Learning Multi-domain Convolutional Neural Networks for Visual Tracking
inferredcites →https://doi.org/10.1109/cvpr.2016.85openalex-snapshot
A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.87openalex-snapshot
Bilateral Space Video Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2011.6126471openalex-snapshot
Key-segments for video object segmentation
inferredcites →https://doi.org/10.1109/iccv.2013.223openalex-snapshot
Fast Object Segmentation in Unconstrained Video
inferredcites →https://doi.org/10.1109/iccv.2015.164openalex-snapshot
Holistically-Nested Edge Detection
inferredcites →https://doi.org/10.1109/iccv.2015.178openalex-snapshot
Learning Deconvolution Network for Semantic Segmentation
inferredcites →https://doi.org/10.1109/iccv.2015.369openalex-snapshot
Fully Connected Object Proposals for Video Segmentation
inferredcites →https://doi.org/10.1109/iccv.2015.370openalex-snapshot
Video Segmentation with Just a Few Strokes
inferredcites →https://doi.org/10.1109/iccv.2015.65openalex-snapshot
High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and Its Applications to High-Level Vision
inferredcites →https://doi.org/10.1109/iccvw.2015.79openalex-snapshot
The Visual Object Tracking VOT2015 Challenge Results
inferredcites →https://doi.org/10.1109/tpami.2010.161openalex-snapshot
Contour Detection and Hierarchical Image Segmentation
inferredcites →https://doi.org/10.1109/tpami.2012.231openalex-snapshot
Learning Hierarchical Features for Scene Labeling
inferredcites →https://doi.org/10.1109/tpami.2013.242openalex-snapshot
Segmentation of Moving Objects by Long Term Video Analysis
inferredcites →https://doi.org/10.1109/tpami.2016.2537320openalex-snapshot
Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation
inferredcites →https://doi.org/10.1109/tpami.2016.2572683openalex-snapshot
Fully Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1511.07386openalex-snapshot
Pushing the Boundaries of Boundary Detection using Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1512.03385openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1605.06409openalex-snapshot
R-FCN: Object Detection via Region-based Fully Convolutional Networks
inferredcites →https://doi.org/10.48550/arxiv.1612.02646openalex-snapshot
Learning Video Object Segmentation from Static Images
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4837230openalex-extracted
A Novel Ol-Mapping Operator-Based Edge Detection Approach and its Application in Image Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-01219-9_13openalex-snapshot
Unsupervised Video Object Segmentation with Motion-Based Bilateral Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-01219-9_6openalex-snapshot
Video Object Segmentation with Joint Re-identification and Attention-Aware Mask Propagation
inferred← citeshttps://doi.org/10.1007/978-3-030-01225-0_43openalex-snapshot
End-to-End Joint Semantic Segmentation of Actors and Actions in Video
inferred← citeshttps://doi.org/10.1007/978-3-030-01228-1_36openalex-snapshot
YouTube-VOS: Sequence-to-Sequence Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-01234-2_6openalex-snapshot
Switchable Temporal Propagation Network
inferred← citeshttps://doi.org/10.1007/978-3-030-01237-3_4openalex-snapshot
VideoMatch: Matching Based Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-01246-5_39openalex-snapshot
Joint Person Segmentation and Identification in Synchronized First- and Third-Person Videos
inferred← citeshttps://doi.org/10.1007/978-3-030-01252-6_31openalex-snapshot
Video Object Segmentation by Learning Location-Sensitive Embeddings
inferred← citeshttps://doi.org/10.1007/978-3-030-01261-8_24openalex-snapshot
Tracking Emerges by Colorizing Videos
inferred← citeshttps://doi.org/10.1007/978-3-030-01264-9_32openalex-snapshot
Sequential Clique Optimization for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-01449-0_15openalex-snapshot
Foreground Background Segmentation in Front of Changing Footage on a Video Screen
inferred← citeshttps://doi.org/10.1007/978-3-030-03335-4_27openalex-snapshot
Video Saliency Detection Using Deep Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-11018-5_2openalex-snapshot
Video Object Segmentation with Referring Expressions
inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_10openalex-snapshot
Continual Occlusion and Optical Flow Estimation
inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_14openalex-snapshot
Learning from PhotoShop Operation Videos: The PSOV Dataset
inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_32openalex-snapshot
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_35openalex-snapshot
PReMVOS: Proposal-Generation, Refinement and Merging for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_38openalex-snapshot
Unseen Object Segmentation in Videos via Transferable Representations
inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_8openalex-snapshot
Video Object Segmentation with Language Referring Expressions
inferred← citeshttps://doi.org/10.1007/978-3-030-31723-2_35openalex-snapshot
One-Shot Video Object Segmentation Initialized with Referring Expression
inferred← citeshttps://doi.org/10.1007/978-3-030-31723-2_37openalex-snapshot
Lightweight Video Object Segmentation Based on ConvGRU
inferred← citeshttps://doi.org/10.1007/978-3-030-33391-1_22openalex-snapshot
A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Image Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-33676-9_22openalex-snapshot
Visual Coin-Tracking: Tracking of Planar Double-Sided Objects
inferred← citeshttps://doi.org/10.1007/978-3-030-33676-9_37openalex-snapshot
Localized Interactive Instance Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-34120-6_31openalex-snapshot
Enhanced Video Segmentation with Object Tracking
inferred← citeshttps://doi.org/10.1007/978-3-030-36189-1_2openalex-snapshot
Adaptive Online Learning for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-36711-4_43openalex-snapshot
Motion-Based Occlusion-Aware Pixel Graph Network for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-37734-2_7openalex-snapshot
A New Local Transformation Module for Few-Shot Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-41404-7_13openalex-snapshot
Deep Similarity Fusion Networks for One-Shot Semantic Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-41816-8_8openalex-snapshot
Reconstructing 3D Human Avatars from Monocular Images
inferred← citeshttps://doi.org/10.1007/978-3-030-42128-1_1openalex-snapshot
Unsupervised Visual Learning: From Pixels to Seeing
inferred← citeshttps://doi.org/10.1007/978-3-030-42128-1_6openalex-snapshot
Coupling Appearance and Motion: Unsupervised Clustering for Object Segmentation Through Space and Time
inferred← citeshttps://doi.org/10.1007/978-3-030-49161-1_27openalex-snapshot
Joint Multi-object Detection and Segmentation from an Untrimmed Video
inferred← citeshttps://doi.org/10.1007/978-3-030-50020-7_31openalex-snapshot
Augmented Reality Fashion Show Using Personalized 3D Human Models
inferred← citeshttps://doi.org/10.1007/978-3-030-50347-5_17openalex-snapshot
A Semantics-Guided Warping for Semi-supervised Video Object Instance Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-50347-5_19openalex-snapshot
Video Object Segmentation Using Convex Optimization of Foreground and Background Distributions
inferred← citeshttps://doi.org/10.1007/978-3-030-58517-4_34openalex-snapshot
Continuous Adaptation for Interactive Object Segmentation by Learning from Corrections
inferred← citeshttps://doi.org/10.1007/978-3-030-58520-4_18openalex-snapshot
Interactive Video Object Segmentation Using Global and Local Transfer Modules
inferred← citeshttps://doi.org/10.1007/978-3-030-58536-5_46openalex-snapshot
Learning What to Learn for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-58542-6_38openalex-snapshot
Kernelized Memory Network for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-58555-6_11openalex-snapshot
Memory Selection Network for Video Propagation
inferred← citeshttps://doi.org/10.1007/978-3-030-58555-6_13openalex-snapshot
URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark
inferred← citeshttps://doi.org/10.1007/978-3-030-58558-7_20openalex-snapshot
Collaborative Video Object Segmentation by Foreground-Background Integration
inferred← citeshttps://doi.org/10.1007/978-3-030-58558-7_26openalex-snapshot
TAO: A Large-Scale Benchmark for Tracking Any Object
inferred← citeshttps://doi.org/10.1007/978-3-030-58568-6_29openalex-snapshot
Unsupervised Video Object Segmentation with Joint Hotspot Tracking
inferred← citeshttps://doi.org/10.1007/978-3-030-58571-6_18openalex-snapshot
Learning Object Depth from Camera Motion and Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-58580-8_39openalex-snapshot
Video Object Segmentation with Episodic Graph Memory Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-58586-0_7openalex-snapshot
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
inferred← citeshttps://doi.org/10.1007/978-3-030-58601-0_18openalex-snapshot
ScribbleBox: Interactive Annotation Framework for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-58607-2_43openalex-snapshot
Fast Video Object Segmentation Using the Global Context Module
inferred← citeshttps://doi.org/10.1007/978-3-030-58621-8_10openalex-snapshot
STEm-Seg: Spatio-Temporal Embeddings for Instance Segmentation in Videos
inferred← citeshttps://doi.org/10.1007/978-3-030-60633-6_45openalex-snapshot
Aggregating Spatio-temporal Context for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-66125-0_2openalex-snapshot
MaskADNet: MOTS Based on ADNet
inferred← citeshttps://doi.org/10.1007/978-3-030-69525-5_37openalex-snapshot
Mask-Ranking Network for Semi-supervised Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-69532-3_30openalex-snapshot
Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-88004-0_13openalex-snapshot
Joint Attention Mechanism for Unsupervised Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-88013-2_27openalex-snapshot
Dual Attention Based Network with Hierarchical ConvLSTM for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-02375-0_20openalex-snapshot
COMatchNet: Co-Attention Matching Network for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-06381-7_14openalex-snapshot
Video Object Segmentation Based on Guided Feature Transfer Learning
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Style-Guided Shadow Removal
inferred← citeshttps://doi.org/10.1007/978-3-031-19815-1_37openalex-snapshot
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
inferred← citeshttps://doi.org/10.1007/978-3-031-19818-2_27openalex-snapshot
Learning Quality-aware Dynamic Memory for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-19818-2_35openalex-snapshot
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-19818-2_37openalex-snapshot
Global Spectral Filter Memory Network for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-19821-2_6openalex-snapshot
Semantic-Aware Fine-Grained Correspondence
inferred← citeshttps://doi.org/10.1007/978-3-031-20047-2_33openalex-snapshot
Robust Visual Tracking by Segmentation
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Introduction to Deep Learning
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Rethinking RNN-Based Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-26293-7_35openalex-snapshot
Video Object Segmentation via Structural Feature Reconfiguration
inferred← citeshttps://doi.org/10.1007/978-3-031-26316-3_28openalex-snapshot
A Compressive Prior Guided Mask Predictive Coding Approach for Video Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-30111-7_9openalex-snapshot
Spatial and Temporal Guidance for Semi-supervised Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-31407-0_31openalex-snapshot
Multi-modality Fusion for Siamese Network Based RGB-T Tracking (mfSiamTrack)
inferred← citeshttps://doi.org/10.1007/978-3-031-44195-0_41openalex-snapshot
Self-supervised Video Object Segmentation Using Motion Feature Compensation
inferred← citeshttps://doi.org/10.1007/978-3-031-44237-7_26openalex-snapshot
Fast Context Adaptation for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-44521-7_1openalex-snapshot
Ultrasound Video Segmentation with Adaptive Temporal Memory
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PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation
inferred← citeshttps://doi.org/10.1007/978-3-031-72855-6_6openalex-snapshot
Spatial-Temporal Multi-level Association for Video Object Segmentation
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Improving Video Segmentation via Dynamic Anchor Queries
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Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object Segmentation
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GiT: Towards Generalist Vision Transformer Through Universal Language Interface
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OneVOS: Unifying Video Object Segmentation with All-in-One Transformer Framework
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Video-Based Semi-automatic Drivable Area Segmentation
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Enhancing Video and Image Analysis with SAM2: Experimental Insights for Diverse Applications
inferred← citeshttps://doi.org/10.1007/978-3-032-31666-0_5openalex-snapshot
Mamba-VOS: Efficient Video Object Segmentation with Selective State Space Models
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Sparsely Supervised Surgical Video Segmentation with Reliable Asymmetric Dual Memory
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Measuring the Accuracy of Object Detectors and Trackers
inferred← citeshttps://doi.org/10.1007/978-3-319-70087-8_69openalex-snapshot
Generic Pixel Level Object Tracker Using Bi-Channel Fully Convolutional Network
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TCCF: Tracking Based on Convolutional Neural Network and Correlation Filters
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Spectral Context Matching for Video Object Segmentation Under Occlusion
inferred← citeshttps://doi.org/10.1007/978-981-13-0020-2_32openalex-snapshot
Deep Neural Network for Foreground Object Segmentation: An Unsupervised Approach
inferred← citeshttps://doi.org/10.1007/978-981-13-0020-2_4openalex-snapshot
Flow-Free Video Object Segmentation
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Keyframes and Shot Boundaries: The Attributes of Scene Segmentation and Classification
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A Discriminative Feature Learning Based on Deep Residual Network for Face Verification
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A Review on Video Analytics Its Challenges and Applications
inferred← citeshttps://doi.org/10.1007/978-981-16-7189-0_9openalex-snapshot
Simultaneously Predicting Video Object Segmentation and Optical Flow Without Motion Annotations
inferred← citeshttps://doi.org/10.1007/978-981-19-1253-5_6openalex-snapshot
Attention-Guided Memory Model for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-981-19-4546-5_34openalex-snapshot
A Semi-supervised Video Object Segmentation Method Based on Adaptive Memory Module
inferred← citeshttps://doi.org/10.1007/978-981-19-8915-5_14openalex-snapshot
A Meta-learning-Based Object Detection Method for Custom Grasping in Human-Robot Collaboration
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Agent-SAM-I2V: Self-correcting Promptable Video Segmentation via Agentic Drift Detection and Multi-Prompt Fusion
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Rotated Box-Aware Segmentation for Fixed-Wing UAVs: A PCA-Enhanced SiamMask Approach
inferred← citeshttps://doi.org/10.1007/978-981-95-7664-7_42openalex-snapshot
Infrared Small Target Recognition of UAVs Using CMSCM-LSTM-Unet Architecture
inferred← citeshttps://doi.org/10.1007/978-981-96-0901-7_24openalex-snapshot
Strike the Balance: On-the-Fly Uncertainty Based User Interactions for Long-Term Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-981-96-2260-3_52openalex-snapshot
Source-Free One-Shot Infrared Video Object Segmentation Based on the Segment Anything Model
inferred← citeshttps://doi.org/10.1007/978-981-96-4170-3_28openalex-snapshot
Moving Object Detection and Segmentation for Various Surveillance Application Using Deep Learning Approaches in Explainable Artificial Intelligence
inferred← citeshttps://doi.org/10.1007/978-981-96-9949-0_13openalex-snapshot
Granularity-Aware Segment and Track for Click Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-981-97-0293-0_7openalex-snapshot
Enhancing Security Surveillance Through Business Intelligence with NVIDIA DeepStream
inferred← citeshttps://doi.org/10.1007/978-981-97-8505-6_6openalex-snapshot
PRM: A Pixel-Region-Matching Approach for Fast Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-981-97-9933-6_7openalex-snapshot
Graph Neural Networks for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/978-981-99-6882-4_14openalex-snapshot
Fast Video Object Segmentation Network Based on Multi-scale Attention Feature Fusion
inferred← citeshttps://doi.org/10.1007/s00138-022-01278-xopenalex-snapshot
Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation
inferred← citeshttps://doi.org/10.1007/s00138-022-01348-0openalex-snapshot
Motion-region annotation for complex videos via label propagation across occluders
inferred← citeshttps://doi.org/10.1007/s00138-024-01524-4openalex-snapshot
Kernel based local matching network for video object segmentation
inferred← citeshttps://doi.org/10.1007/s00371-022-02638-4openalex-snapshot
Spatio-temporal compression for semi-supervised video object segmentation
inferred← citeshttps://doi.org/10.1007/s00371-023-03061-zopenalex-snapshot
Portrait matting using an attention-based memory network
inferred← citeshttps://doi.org/10.1007/s00371-025-03957-yopenalex-snapshot
Boosting memory network for video object segmentation in complex scenes
inferred← citeshttps://doi.org/10.1007/s00521-019-04093-0openalex-snapshot
SPN: short path network for scene text detection
inferred← citeshttps://doi.org/10.1007/s00521-021-06684-2openalex-snapshot
CariesNet: a deep learning approach for segmentation of multi-stage caries lesion from oral panoramic X-ray image
inferred← citeshttps://doi.org/10.1007/s00521-023-09325-yopenalex-snapshot
Few-shot video object segmentation with prototype evolution
inferred← citeshttps://doi.org/10.1007/s00521-024-10661-wopenalex-snapshot
Sufficient learning: mining denser high-quality pixel-level labels for edge detection
inferred← citeshttps://doi.org/10.1007/s00530-025-01825-2openalex-snapshot
Causalseg: investigating causality modeling for semi-supervised video object segmentation
inferred← citeshttps://doi.org/10.1007/s00530-025-02036-5openalex-snapshot
Shadow feature refinement network: progressive feature refinement based on knowledge distillation for effective shadow removal
inferred← citeshttps://doi.org/10.1007/s10444-024-10170-3openalex-snapshot
Augmented Lagrangian method for tensor low-rank and sparsity models in multi-dimensional image recovery
inferred← citeshttps://doi.org/10.1007/s10462-021-10061-9openalex-snapshot
Deep reinforcement learning in computer vision: a comprehensive survey
inferred← citeshttps://doi.org/10.1007/s10462-022-10176-7openalex-snapshot
Deep learning for video object segmentation: a review
inferred← citeshttps://doi.org/10.1007/s10489-021-02547-4openalex-snapshot
A temporal attention based appearance model for video object segmentation
inferred← citeshttps://doi.org/10.1007/s10489-021-02896-0openalex-snapshot
A semi-automated system for person re-identification adaptation to cross-outfit and cross-posture scenarios
inferred← citeshttps://doi.org/10.1007/s10489-021-03015-9openalex-snapshot
Learning bi-grained cross-correlation siamese networks for visual tracking
inferred← citeshttps://doi.org/10.1007/s10489-022-03693-zopenalex-snapshot
Video object segmentation based on temporal frame context information fusion and feature enhancement
inferred← citeshttps://doi.org/10.1007/s10489-022-04072-4openalex-snapshot
Match them up: visually explainable few-shot image classification
inferred← citeshttps://doi.org/10.1007/s10489-024-05486-yopenalex-snapshot
Learning spatiotemporal relationships with a unified framework for video object segmentation
inferred← citeshttps://doi.org/10.1007/s10489-024-05840-0openalex-snapshot
Siam2C: Siamese visual segmentation and tracking with classification-rank loss and classification-aware
inferred← citeshttps://doi.org/10.1007/s10845-026-02973-6openalex-snapshot
Domain-specific adaptation: low-rank adaptation fine-tuning of SAM 2 for manufacturing processes
inferred← citeshttps://doi.org/10.1007/s10846-018-0958-6openalex-snapshot
An Adaptive Robotic System for Doing Pick and Place Operations with Deformable Objects
inferred← citeshttps://doi.org/10.1007/s11042-017-5460-9openalex-snapshot
End-to-end video background subtraction with 3d convolutional neural networks
inferred← citeshttps://doi.org/10.1007/s11042-019-08146-3openalex-snapshot
Effective online refinement for video object segmentation
inferred← citeshttps://doi.org/10.1007/s11042-019-08388-1openalex-snapshot
PerSeg : segmenting salient objects from bag of single image perturbations
inferred← citeshttps://doi.org/10.1007/s11042-019-7219-yopenalex-snapshot
Exploiting weak mask representation with convolutional neural networks for accurate object tracking
inferred← citeshttps://doi.org/10.1007/s11042-019-7569-5openalex-snapshot
Data augmentation of random grid-hiding for video object segmentation
inferred← citeshttps://doi.org/10.1007/s11042-021-10536-5openalex-snapshot
Res2-UNeXt: a novel deep learning framework for few-shot cell image segmentation
inferred← citeshttps://doi.org/10.1007/s11042-021-11126-1openalex-snapshot
Towards general object-based video forgery detection via dual-stream networks and depth information embedding
inferred← citeshttps://doi.org/10.1007/s11042-021-11383-0openalex-snapshot
Content modification of soccer videos using a supervised deep learning framework
inferred← citeshttps://doi.org/10.1007/s11042-022-12981-2openalex-snapshot
Video object segmentation guided refinement on foreground-background objects
inferred← citeshttps://doi.org/10.1007/s11042-023-14361-wopenalex-snapshot
Video object segmentation through semantic visual words matching
inferred← citeshttps://doi.org/10.1007/s11042-023-15369-yopenalex-snapshot
Rational 3D object placement based on deep learning based plane detection
inferred← citeshttps://doi.org/10.1007/s11042-023-16417-3openalex-snapshot
A systematic review of deep learning frameworks for moving object segmentation
inferred← citeshttps://doi.org/10.1007/s11042-023-17260-2openalex-snapshot
Smoke semantic segmentation with multi-scale residual paths and weighted middle surveillances
inferred← citeshttps://doi.org/10.1007/s11042-026-21444-xopenalex-snapshot
An improved semi-supervised video object segmentation and tracking algorithm for real-time applications
inferred← citeshttps://doi.org/10.1007/s11063-019-10110-zopenalex-snapshot
Unsupervised Video Object Segmentation Based on Mixture Models and Saliency Detection
inferred← citeshttps://doi.org/10.1007/s11063-023-11257-6openalex-snapshot
Adaptive Guidance and Attention-Refined Network for Fast Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/s11063-024-11626-9openalex-snapshot
DynamicAug: Enhancing Transfer Learning Through Dynamic Data Augmentation Strategies Based on Model State
inferred← citeshttps://doi.org/10.1007/s11227-023-05637-xopenalex-snapshot
Saliency-based dual-attention network for unsupervised video object segmentation
inferred← citeshttps://doi.org/10.1007/s11227-026-08781-2openalex-snapshot
Enhanced Object tracking in videos: integrating CEDSegNet with adjusted covariance-based mean shift algorithm
inferred← citeshttps://doi.org/10.1007/s11263-018-01141-5openalex-snapshot
Online Mutual Foreground Segmentation for Multispectral Stereo Videos
inferred← citeshttps://doi.org/10.1007/s11263-018-1130-2openalex-snapshot
Face Mask Extraction in Video Sequence
inferred← citeshttps://doi.org/10.1007/s11263-019-01164-6openalex-snapshot
Lucid Data Dreaming for Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/s11263-019-01212-1openalex-snapshot
Tracking Persons-of-Interest via Unsupervised Representation Adaptation
inferred← citeshttps://doi.org/10.1007/s11263-019-01224-xopenalex-snapshot
VOSTR: Video Object Segmentation via Transferable Representations
inferred← citeshttps://doi.org/10.1007/s11263-019-01246-5openalex-snapshot
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos
inferred← citeshttps://doi.org/10.1007/s11263-022-01655-zopenalex-snapshot
Exploring the Semi-Supervised Video Object Segmentation Problem from a Cyclic Perspective
inferred← citeshttps://doi.org/10.1007/s11263-024-02261-xopenalex-snapshot
Audio-Visual Segmentation with Semantics
inferred← citeshttps://doi.org/10.1007/s11263-025-02390-xopenalex-snapshot
Temporal Transductive Inference for Few-Shot Video Object Segmentation
inferred← citeshttps://doi.org/10.1007/s11390-020-0246-3openalex-snapshot
Automatic Video Segmentation Based on Information Centroid and Optimized SaliencyCut
inferred← citeshttps://doi.org/10.1007/s11432-021-3396-7openalex-snapshot
Fast target-aware learning for few-shot video object segmentation
inferred← citeshttps://doi.org/10.1007/s11760-023-02827-1openalex-snapshot
SiamMaskAttn: inverted residual attention block fusing multi-scale feature information for multitask visual object tracking networks
inferred← citeshttps://doi.org/10.1007/s11760-024-03121-4openalex-snapshot
Video smoke detection method based on cell root–branch structure
inferred← citeshttps://doi.org/10.1007/s40747-025-01900-1openalex-snapshot
Parameter-efficient weakly supervised referring video object segmentation via chain-of-thought reasoning
inferred← citeshttps://doi.org/10.1007/s41095-019-0145-0openalex-snapshot
Object removal from complex videos using a few annotations
inferred← citeshttps://doi.org/10.1007/s41095-020-0156-xopenalex-snapshot
WaterNet: An adaptive matching pipeline for segmenting water with volatile appearance
inferred← citeshttps://doi.org/10.1007/s41095-021-0262-4openalex-snapshot
Full-duplex strategy for video object segmentation
inferred← citeshttps://doi.org/10.1007/s41095-022-0282-8openalex-snapshot
Global video object segmentation with spatial constraint module
inferred← citeshttps://doi.org/10.1007/s41745-019-0099-3openalex-snapshot
Beyond Supervised Learning: A Computer Vision Perspective
inferred← citeshttps://doi.org/10.1007/s41870-023-01408-2openalex-snapshot
Mathematical analysis behind occlusion handling in image with deep learning
inferred← citeshttps://doi.org/10.1016/j.asoc.2019.106049openalex-snapshot
Unified model for interpreting multi-view echocardiographic sequences without temporal information
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.112837openalex-snapshot
Vanishing mask refinement in semi-supervised video object segmentation
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102646openalex-snapshot
Automatic vessel segmentation in X-ray angiogram using spatio-temporal fully-convolutional neural network
inferred← citeshttps://doi.org/10.1016/j.compag.2020.105761openalex-snapshot
Video analytic system for detecting cow structure
inferred← citeshttps://doi.org/10.1016/j.compag.2025.110438openalex-snapshot
FiVOS: A fish segmentation algorithm based on interactive video object segmentation and filter enhancement
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106454openalex-snapshot
Self-mentoring: A new deep learning pipeline to train a self-supervised U-net for few-shot learning of bio-artificial capsule segmentation
inferred← citeshttps://doi.org/10.1016/j.cosrev.2021.100379openalex-snapshot
A survey on deep learning and its applications
inferred← citeshttps://doi.org/10.1016/j.cviu.2021.103240openalex-snapshot
MAIN: Multi-Attention Instance Network for video segmentation
inferred← citeshttps://doi.org/10.1016/j.cviu.2023.103812openalex-snapshot
Generalized Framework for Image and Video Object Segmentation Using Affinity Learning and Message Passing Gnns
inferred← citeshttps://doi.org/10.1016/j.cviu.2023.103860openalex-snapshot
CT-VOS: Cutout prediction and tagging for self-supervised video object segmentation
inferred← citeshttps://doi.org/10.1016/j.cviu.2024.103943openalex-snapshot
Space–time recurrent memory network
inferred← citeshttps://doi.org/10.1016/j.cviu.2026.104857openalex-snapshot
Redundancy-aware memory update for improved video object segmentation
inferred← citeshttps://doi.org/10.1016/j.dsp.2021.103309openalex-snapshot
Learning edges and adaptive surroundings for discriminant segmentation tracking
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107325openalex-snapshot
AI-based optical-thermal video data fusion for near real-time blade segmentation in normal wind turbine operation
inferred← citeshttps://doi.org/10.1016/j.eswa.2020.114153openalex-snapshot
Video object segmentation based on motion-aware ROI prediction and adaptive reference updating
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.116704openalex-snapshot
A cascade approach for automatic segmentation of cardiac structures in short-axis cine-MR images using deep neural networks
inferred← citeshttps://doi.org/10.1016/j.future.2019.05.035openalex-snapshot
A unified two-parallel-branch deep neural network for joint gland contour and segmentation learning
inferred← citeshttps://doi.org/10.1016/j.future.2022.05.014openalex-snapshot
A survey of human-in-the-loop for machine learning
inferred← citeshttps://doi.org/10.1016/j.ijleo.2020.166251openalex-snapshot
Efficient foreground object segmentation from video by Probability Weighted Moments
inferred← citeshttps://doi.org/10.1016/j.image.2019.02.011openalex-snapshot
Prototype adjustment for zero shot classification
inferred← citeshttps://doi.org/10.1016/j.image.2020.115858openalex-snapshot
Video object tracking and segmentation with box annotation
inferred← citeshttps://doi.org/10.1016/j.image.2021.116373openalex-snapshot
Fast pixel-matching for video object segmentation
inferred← citeshttps://doi.org/10.1016/j.image.2021.116442openalex-snapshot
CTU depth decision algorithms for HEVC: A survey
inferred← citeshttps://doi.org/10.1016/j.image.2025.117456openalex-snapshot
Video object segmentation based on feature compression and attention correction
inferred← citeshttps://doi.org/10.1016/j.imavis.2019.103864openalex-snapshot
Flow Adaptive Video Object Segmentation
inferred← citeshttps://doi.org/10.1016/j.ins.2019.07.004openalex-snapshot
Masked and dynamic Siamese network for robust visual tracking
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