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Primary Object Segmentation in Videos Based on Region Augmentation and Reduction

https://doi.org/10.1109/cvpr.2017.784

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-15555-0_21openalex-snapshot

Object Segmentation by Long Term Analysis of Point Trajectories

inferredcites →https://doi.org/10.1007/s11263-013-0620-5openalex-snapshot

Selective Search for Object Recognition

inferredcites →https://doi.org/10.1016/j.jvcir.2015.12.011openalex-snapshot

Compressed domain video saliency detection using global and local spatiotemporal features

inferredcites →https://doi.org/10.1016/j.jvcir.2016.02.001openalex-snapshot

Finding spatio-temporal salient paths for video objects discovery

inferredcites →https://doi.org/10.1109/cvpr.2005.16openalex-snapshot

A Bayesian Hierarchical Model for Learning Natural Scene Categories

inferredcites →https://doi.org/10.1109/cvpr.2012.6247728openalex-snapshot

Higher order motion models and spectral clustering

inferredcites →https://doi.org/10.1109/cvpr.2012.6247735openalex-snapshot

Maximum weight cliques with mutex constraints for video object 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.2013.267openalex-snapshot

A Video Representation Using Temporal Superpixels

inferredcites →https://doi.org/10.1109/cvpr.2013.87openalex-snapshot

Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions

inferredcites →https://doi.org/10.1109/cvpr.2014.444openalex-snapshot

Region-Based Particle Filter for Video Object Segmentation

inferredcites →https://doi.org/10.1109/cvpr.2014.55openalex-snapshot

SeamSeg: Video Object Segmentation Using Patch Seams

inferredcites →https://doi.org/10.1109/cvpr.2015.7298873openalex-snapshot

Learning to detect Motion Boundaries

inferredcites →https://doi.org/10.1109/cvpr.2015.7298961openalex-snapshot

Saliency-aware geodesic video object segmentation

inferredcites →https://doi.org/10.1109/cvpr.2015.7299012openalex-snapshot

Object proposal by multi-branch hierarchical segmentation

inferredcites →https://doi.org/10.1109/cvpr.2016.107openalex-snapshot

Track and Segment: An Iterative Unsupervised Approach for Video Object Proposals

inferredcites →https://doi.org/10.1109/cvpr.2016.121openalex-snapshot

POD: Discovering Primary Objects in Videos Based on Evolutionary Refinement of Object Recurrence, Background, and Primary Object Models

inferredcites →https://doi.org/10.1109/cvpr.2016.423openalex-snapshot

Video Segmentation via Object Flow

inferredcites →https://doi.org/10.1109/cvpr.2016.615openalex-snapshot

Efficient Coarse-to-Fine Patch Match for Large Displacement Optical Flow

inferredcites →https://doi.org/10.1109/cvpr.2016.82openalex-snapshot

Primary Object Segmentation in Videos via Alternate Convex Optimization of Foreground and Background Distributions

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/iccv.1998.710861openalex-snapshot

Motion segmentation and tracking using normalized cuts

inferredcites →https://doi.org/10.1109/iccv.2011.6126418openalex-snapshot

Object segmentation in video: A hierarchical variational approach for turning point trajectories into dense regions

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.2013.231openalex-snapshot

Structured Forests for Fast Edge Detection

inferredcites →https://doi.org/10.1109/iccv.2013.273openalex-snapshot

Video Segmentation by Tracking Many Figure-Ground Segments

inferredcites →https://doi.org/10.1109/iccv.2015.369openalex-snapshot

Fully Connected Object Proposals for Video Segmentation

inferredcites →https://doi.org/10.1109/iccv.2015.501openalex-snapshot

Self-Occlusions and Disocclusions in Causal Video Object Segmentation

inferredcites →https://doi.org/10.1109/tcsvt.2015.2433171openalex-snapshot

Discovering Primary Objects in Videos by Saliency Fusion and Iterative Appearance Estimation

inferredcites →https://doi.org/10.1109/tip.2015.2479918openalex-snapshot

Video Stabilization Based on Feature Trajectory Augmentation and Selection and Robust Mesh Grid Warping

inferredcites →https://doi.org/10.1109/tip.2015.2500820openalex-snapshot

Fast Appearance Modeling for Automatic Primary Video Object Segmentation

inferredcites →https://doi.org/10.1109/tpami.2010.161openalex-snapshot

Contour Detection and Hierarchical Image Segmentation

inferredcites →https://doi.org/10.1145/1015706.1015720openalex-snapshot

"GrabCut"

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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/10.1007/978-3-030-01246-5_39openalex-snapshot

Joint Person Segmentation and Identification in Synchronized First- and Third-Person Videos

inferred← citeshttps://doi.org/10.1007/978-3-030-01246-5_48openalex-snapshot

Unsupervised Video Object Segmentation Using Motion Saliency-Guided Spatio-Temporal Propagation

inferred← citeshttps://doi.org/10.1007/978-3-030-01252-6_44openalex-snapshot

Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection

inferred← citeshttps://doi.org/10.1007/978-3-030-01264-9_32openalex-snapshot

Sequential Clique Optimization for Video Object Segmentation

inferred← citeshttps://doi.org/10.1007/978-3-030-20870-7_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_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/10.1007/978-3-030-42128-1_6openalex-snapshot

Coupling Appearance and Motion: Unsupervised Clustering for Object Segmentation Through Space and Time

inferred← citeshttps://doi.org/10.1007/978-3-030-58520-4_18openalex-snapshot

Interactive Video Object Segmentation Using Global and Local Transfer Modules

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/10.1007/978-3-030-58580-8_39openalex-snapshot

Video Object Segmentation with Episodic Graph Memory Networks

inferred← citeshttps://doi.org/10.1007/978-3-030-58583-9_27openalex-snapshot

Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation

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/10.1007/978-3-030-69532-3_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/10.1007/978-3-031-16788-1_15openalex-snapshot

Improving Unsupervised Label Propagation for Pose Tracking and Video Object Segmentation

inferred← citeshttps://doi.org/10.1007/978-3-031-44656-6_2openalex-snapshot

VOS

inferred← citeshttps://doi.org/10.1007/978-3-031-76607-7_12openalex-snapshot

Towards Interactive Video Segmentation by Dynamic and Iterative Spanning Forest

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/10.1007/978-981-99-8537-1_14openalex-snapshot

Asymmetric Attention Fusion for Unsupervised Video Object Segmentation

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Improving communication skills of children with autism through support of applied behavioral analysis treatments using multimedia computing: a survey

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Deep reinforcement learning in computer vision: a comprehensive survey

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/s11042-019-08146-3openalex-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/s11042-019-08438-8openalex-snapshot

Superpixels for image and video processing based on proximity-weighted patch matching

inferred← citeshttps://doi.org/10.1007/s11063-023-11395-xopenalex-snapshot

Multi-scale Deep Feature Transfer for Automatic Video Object Segmentation

inferred← citeshttps://doi.org/10.1007/s11263-018-1122-2openalex-snapshot

Learning to Segment Moving Objects

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/s11263-023-01859-xopenalex-snapshot

The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields

inferred← citeshttps://doi.org/10.1007/s11263-024-02024-8openalex-snapshot

Adaptive Multi-Source Predictor for Zero-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.1007/s11571-024-10068-2openalex-snapshot

A spatiotemporal energy model based on spiking neurons for human motion perception

inferred← citeshttps://doi.org/10.1007/s13042-022-01615-6openalex-snapshot

Unsupervised video object segmentation: an affinity and edge learning approach

inferred← citeshttps://doi.org/10.1007/s41095-021-0262-4openalex-snapshot

Full-duplex strategy for video object 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.imavis.2019.103864openalex-snapshot

Flow Adaptive Video Object Segmentation

inferred← citeshttps://doi.org/10.1016/j.jvcir.2018.05.018openalex-snapshot

Photographic composition classification and dominant geometric element detection for outdoor scenes

inferred← citeshttps://doi.org/10.1016/j.jvcir.2020.102953openalex-snapshot

Unsupervised video object segmentation with distractor-aware online adaptation

inferred← citeshttps://doi.org/10.1016/j.jvcir.2021.103293openalex-snapshot

Video object segmentation via random walks on two-frame graphs comprising superpixels

inferred← citeshttps://doi.org/10.1016/j.neucom.2019.01.003openalex-snapshot

Refined video segmentation through global appearance regression

inferred← citeshttps://doi.org/10.1016/j.neucom.2020.03.020openalex-snapshot

Higher-order potentials for video object segmentation in bilateral space

inferred← citeshttps://doi.org/10.1049/iet-ipr.2019.0836openalex-snapshot

Flow driven attention network for video salient object detection

inferred← citeshttps://doi.org/10.1088/1742-6596/1530/1/012090openalex-snapshot

Inserting Virtual Static Object with Geometry Consistency into Real Video

inferred← citeshttps://doi.org/10.1109/access.2018.2838442openalex-snapshot

Multiscale Feature Extractors for Stereo Matching Cost Computation

inferred← citeshttps://doi.org/10.1109/access.2019.2933479openalex-snapshot

Online Semantic Object Segmentation for Vision Robot Collected Video

inferred← citeshttps://doi.org/10.1109/access.2019.2940768openalex-snapshot

Cascaded ConvLSTMs Using Semantically-Coherent Data Synthesis for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/access.2020.2971964openalex-snapshot

Video Object Segmentation by Latent Outcome Regression

inferred← citeshttps://doi.org/10.1109/access.2021.3132453openalex-snapshot

A Reinforcement Learning Based Adaptive ROI Generation for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/access.2022.3201245openalex-snapshot

Local Memory Read-and-Comparator for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/avss.2019.8909894openalex-snapshot

Graph-to-Graph Energy Minimization for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cbmi.2019.8877438openalex-snapshot

On guiding video object segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00060openalex-snapshot

The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00125openalex-snapshot

MoNet: Deep Motion Exploitation for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00130openalex-snapshot

Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00152openalex-snapshot

Motion-Guided Cascaded Refinement Network for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00683openalex-snapshot

Instance Embedding Transfer to Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00774openalex-snapshot

Fast and Accurate Online Video Object Segmentation via Tracking Parts

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00946openalex-snapshot

Reinforcement Cutting-Agent Learning for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2019.00097openalex-snapshot

Unsupervised Moving Object Detection via Contextual Information Separation

inferred← citeshttps://doi.org/10.1109/cvpr.2019.00147openalex-snapshot

Spatiotemporal CNN for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr.2019.00318openalex-snapshot

Learning Unsupervised Video Object Segmentation Through Visual Attention

inferred← citeshttps://doi.org/10.1109/cvpr.2019.00374openalex-snapshot

See More, Know More: Unsupervised Video Object Segmentation With Co-Attention Siamese Networks

inferred← citeshttps://doi.org/10.1109/cvpr.2019.00542openalex-snapshot

RVOS: End-To-End Recurrent Network for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.00898openalex-snapshot

Learning Video Object Segmentation From Unlabeled Videos

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00285openalex-snapshot

DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.00724openalex-snapshot

Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

inferred← citeshttps://doi.org/10.1109/cvpr46437.2021.01520openalex-snapshot

Reciprocal Transformations for Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/cvpr52688.2022.00268openalex-snapshot

Deformable Sprites for Unsupervised Video Decomposition

inferred← citeshttps://doi.org/10.1109/cvpr52729.2023.01401openalex-snapshot

Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping

inferred← citeshttps://doi.org/10.1109/cvpr52729.2023.02120openalex-snapshot

Unsupervised Space-Time Network for Temporally-Consistent Segmentation of Multiple Motions

inferred← citeshttps://doi.org/10.1109/iccci56745.2023.10128359openalex-snapshot

Unsupervised Online Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iccv.2017.389openalex-snapshot

CDTS: Collaborative Detection, Tracking, and Segmentation for Online Multiple Object Segmentation in Videos

inferred← citeshttps://doi.org/10.1109/iccv.2019.00102openalex-snapshot

Anchor Diffusion for Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iccv.2019.00351openalex-snapshot

Patchwork: A Patch-Wise Attention Network for Efficient Object Detection and Segmentation in Video Streams

inferred← citeshttps://doi.org/10.1109/iccv.2019.00535openalex-snapshot

AMP: Adaptive Masked Proxies for Few-Shot Segmentation

inferred← citeshttps://doi.org/10.1109/iccv.2019.00737openalex-snapshot

Motion Guided Attention for Video Salient Object Detection

inferred← citeshttps://doi.org/10.1109/iccv.2019.00933openalex-snapshot

Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00159openalex-snapshot

Learning Motion-Appearance Co-Attention for Zero-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00285openalex-snapshot

Human Detection and Segmentation via Multi-view Consensus

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00336openalex-snapshot

Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00488openalex-snapshot

Full-Duplex Strategy for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00709openalex-snapshot

Self-supervised Video Object Segmentation by Motion Grouping

inferred← citeshttps://doi.org/10.1109/iccv48922.2021.00866openalex-snapshot

Deep Transport Network for Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iccvw.2019.00187openalex-snapshot

Towards Segmenting Anything That Moves

inferred← citeshttps://doi.org/10.1109/icpr48806.2021.9413239openalex-snapshot

Video semantic segmentation using deep multi-view representation learning

inferred← citeshttps://doi.org/10.1109/icra.2019.8794254openalex-snapshot

Video Object Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting

inferred← citeshttps://doi.org/10.1109/ictc49870.2020.9289608openalex-snapshot

Inter-image Affinity based Interactive Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iros45743.2020.9341737openalex-snapshot

Meta-Learning Deep Visual Words for Fast Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/iros60139.2025.11246064openalex-snapshot

MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking

inferred← citeshttps://doi.org/10.1109/iv48863.2021.9575445openalex-snapshot

Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-Task Baseline

inferred← citeshttps://doi.org/10.1109/jas.2021.1004210openalex-snapshot

Scribble-Supervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/jas.2023.123456openalex-snapshot

Coarse-to-Fine Video Instance Segmentation With Factorized Conditional Appearance Flows

inferred← citeshttps://doi.org/10.1109/tcsvt.2019.2961267openalex-snapshot

Reliable and Dynamic Appearance Modeling and Label Consistency Enforcing for Fast and Coherent Video Object Segmentation With the Bilateral Grid

inferred← citeshttps://doi.org/10.1109/tcsvt.2020.2971641openalex-snapshot

Real Time Video Object Segmentation in Compressed Domain

inferred← citeshttps://doi.org/10.1109/tcsvt.2021.3057872openalex-snapshot

Flow-Edge Guided Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3491214openalex-snapshot

Exploring the Better Correlation for Few-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tencon.2018.8650146openalex-snapshot

Weakly Supervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tip.2018.2859622openalex-snapshot

Joint Video Object Discovery and Segmentation by Coupled Dynamic Markov Networks

inferred← citeshttps://doi.org/10.1109/tip.2019.2930152openalex-snapshot

Unsupervised Online Video Object Segmentation With Motion Property Understanding

inferred← citeshttps://doi.org/10.1109/tip.2020.3013162openalex-snapshot

MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tip.2021.3070200openalex-snapshot

Multi-Stream Attention-Aware Graph Convolution Network for Video Salient Object Detection

inferred← citeshttps://doi.org/10.1109/tip.2021.3113166openalex-snapshot

Joint Multisource Saliency and Exemplar Mechanism for Weakly Supervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tip.2023.3267244openalex-snapshot

Hierarchical Co-Attention Propagation Network for Zero-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tmm.2019.2918720openalex-snapshot

RotateView: A Video Composition System for Interactive Product Display

inferred← citeshttps://doi.org/10.1109/tmm.2020.3020698openalex-snapshot

Learning to Segment Video Object With Accurate Boundaries

inferred← citeshttps://doi.org/10.1109/tmm.2021.3092202openalex-snapshot

Horizontal-to-Vertical Video Conversion

inferred← citeshttps://doi.org/10.1109/tnnls.2019.2963282openalex-snapshot

MASK-RL: Multiagent Video Object Segmentation Framework Through Reinforcement Learning

inferred← citeshttps://doi.org/10.1109/tpami.2018.2819173openalex-snapshot

Semi-Supervised Video Object Segmentation with Super-Trajectories

inferred← citeshttps://doi.org/10.1109/tpami.2018.2838670openalex-snapshot

Video Object Segmentation without Temporal Information

inferred← citeshttps://doi.org/10.1109/tpami.2018.2865794openalex-snapshot

Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos

inferred← citeshttps://doi.org/10.1109/tpami.2018.2881114openalex-snapshot

SPFTN: A Joint Learning Framework for Localizing and Segmenting Objects in Weakly Labeled Videos

inferred← citeshttps://doi.org/10.1109/tpami.2018.2890659openalex-snapshot

Online Meta Adaptation for Fast Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tpami.2019.2906175openalex-snapshot

Motion-Guided Cascaded Refinement Network for Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/tpami.2020.2966453openalex-snapshot

Paying Attention to Video Object Pattern Understanding

inferred← citeshttps://doi.org/10.1109/tpami.2020.3040258openalex-snapshot

Zero-Shot Video Object Segmentation with Co-Attention Siamese Networks

inferred← citeshttps://doi.org/10.1109/tpami.2021.3115815openalex-snapshot

Segmenting Objects From Relational Visual Data

inferred← citeshttps://doi.org/10.1109/tpami.2021.3120228openalex-snapshot

Iterative Knowledge Exchange Between Deep Learning and Space-Time Spectral Clustering for Unsupervised Segmentation in Videos

inferred← citeshttps://doi.org/10.1109/tpami.2021.3123902openalex-snapshot

Self-Supervised Human Detection and Segmentation via Background Inpainting

inferred← citeshttps://doi.org/10.1109/tpami.2022.3198480openalex-snapshot

EM-Driven Unsupervised Learning for Efficient Motion Segmentation

inferred← citeshttps://doi.org/10.1109/tpami.2023.3305122openalex-snapshot

TokenCut: Segmenting Objects in Images and Videos With Self-Supervised Transformer and Normalized Cut

inferred← citeshttps://doi.org/10.1109/wacv.2019.00188openalex-snapshot

Tukey-Inspired Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/wacv45572.2020.9093589openalex-snapshot

EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency

inferred← citeshttps://doi.org/10.1109/wacv48630.2021.00172openalex-snapshot

Mask Selection and Propagation for Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1109/wacv51458.2022.00061openalex-snapshot

Video Salient Object Detection via Contrastive Features and Attention Modules

inferred← citeshttps://doi.org/10.1109/wacv51458.2022.00216openalex-snapshot

Multi-motion and Appearance Self-Supervised Moving Object Detection

inferred← citeshttps://doi.org/10.1109/wacv56688.2023.00584openalex-snapshot

A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.1145/3321507openalex-snapshot

Appearance-consistent Video Object Segmentation Based on a Multinomial Event Model

inferred← citeshttps://doi.org/10.1145/3391743openalex-snapshot

Video Object Segmentation and Tracking

inferred← citeshttps://doi.org/10.1145/3394171.3413934openalex-snapshot

MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos

inferred← citeshttps://doi.org/10.1145/3474085.3475192openalex-snapshot

Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.1145/3474085.3475626openalex-snapshot

SRNet

inferred← citeshttps://doi.org/10.1145/3581783.3612131openalex-snapshot

Fine-grained Key-Value Memory Enhanced Predictor for Video Representation Learning

inferred← citeshttps://doi.org/10.1186/s41074-018-0045-8openalex-snapshot

Supervoxel-based segmentation of 3D imagery with optical flow integration for spatiotemporal processing

inferred← citeshttps://doi.org/10.1609/aaai.v34i07.6718openalex-snapshot

Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection

inferred← citeshttps://doi.org/10.23919/apsipa.2018.8659603openalex-snapshot

Change Detection in High Resolution Satellite Images Using an Ensemble of Convolutional Neural Networks

inferred← citeshttps://doi.org/10.24963/ijcai.2020/69openalex-snapshot

A 3D Convolutional Approach to Spectral Object Segmentation in Space and Time

inferred← citeshttps://doi.org/10.3390/app12157781openalex-snapshot

Complementary Segmentation of Primary Video Objects with Reversible Flows

inferred← citeshttps://doi.org/10.3390/electronics11162612openalex-snapshot

Multimodal CT Image Synthesis Using Unsupervised Deep Generative Adversarial Networks for Stroke Lesion Segmentation

inferred← citeshttps://doi.org/10.3390/electronics11182899openalex-snapshot

Sequential Clique Optimization for Unsupervised and Weakly Supervised Video Object Segmentation

inferred← citeshttps://doi.org/10.3837/tiis.2021.09.007openalex-snapshot

Higher-Order Conditional Random Field established with CNNs for Video Object Segmentation

inferred← citeshttps://doi.org/10.3837/tiis.2024.04.007openalex-snapshot

Dual-stream Co-enhanced Network for Unsupervised Video Object Segmentation

inferred← citeshttps://doi.org/10.3929/ethz-b-000460874openalex-snapshot

Video Object Segmentation with Episodic Graph Memory Networks

inferred← citeshttps://doi.org/10.4218/etrij.2023-0115openalex-snapshot

Background memory‐assisted zero‐shot video object segmentation for unmanned aerial and ground vehicles

inferred← citeshttps://doi.org/10.48550/arxiv.1803.00557openalex-snapshot

The 2018 DAVIS Challenge on Video Object Segmentation

inferred← citeshttps://doi.org/10.48550/arxiv.1811.09521openalex-snapshot

Complementary Segmentation of Primary Video Objects with Reversible Flows

inferred← citeshttps://doi.org/10.48550/arxiv.1901.03360openalex-snapshot

Unsupervised Moving Object Detection via Contextual Information Separation

inferred← citeshttps://doi.org/10.48550/arxiv.1902.11123openalex-snapshot

Adaptive Masked Proxies for Few-Shot Segmentation

inferred← citeshttps://doi.org/10.48550/arxiv.1904.09172openalex-snapshot

Video Object Segmentation and Tracking: A Survey

inferred← citeshttps://doi.org/10.48550/arxiv.1905.00737openalex-snapshot

The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation

inferred← citeshttps://doi.org/10.48550/arxiv.1907.03326openalex-snapshot

Spacetime Graph Optimization for Video Object Segmentation

inferred← citeshttps://doi.org/10.48550/arxiv.1907.08051openalex-snapshot

Self-supervised Training of Proposal-based Segmentation via Background Prediction

inferred← citeshttps://doi.org/10.48550/arxiv.1907.08895openalex-snapshot

An Efficient 3D CNN for Action/Object Segmentation in Video

inferred← citeshttps://doi.org/10.48550/arxiv.1908.10717openalex-snapshot

Fast Video Object Segmentation via Mask Transfer Network

inferred← citeshttps://doi.org/10.48550/arxiv.1912.01373openalex-snapshot

Automatic Video Object Segmentation via Motion-Appearance-Stream Fusion and Instance-aware Segmentation

inferred← citeshttps://doi.org/10.48550/arxiv.2011.05626openalex-snapshot

Self-supervised Segmentation via Background Inpainting

inferred← citeshttps://doi.org/10.48550/arxiv.2011.11630openalex-snapshot

Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation

inferred← citeshttps://doi.org/10.48550/arxiv.2104.07658openalex-snapshot

Self-supervised Video Object Segmentation by Motion Grouping

inferred← citeshttps://doi.org/10.48550/arxiv.2104.10386openalex-snapshot

Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

inferred← citeshttps://doi.org/10.48550/arxiv.2105.10201openalex-snapshot

DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation

inferred← citeshttps://doi.org/10.48550/arxiv.2108.05076openalex-snapshot

Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentation

inferred← citeshttps://doi.org/10.51983/ajcst-2019.8.s2.2020openalex-snapshot

A Study on Image Segmentation Techniques

inferred← citeshttps://doi.org/10.5244/c.34.65openalex-snapshot

Making a Case for 3D Convolutions for Object Segmentation in Videos

inferred← citeshttps://doi.org/10.70675/44a50fa3zc71fz4d80za512zcc3021e0fbeeopenalex-snapshot

Dynamic visual saliency in image sequences

inferred← citeshttps://doi.org/10.70675/9c6ed094z8c91z435fz8111ze1ed33a7fe92openalex-snapshot

Enhancing Human-Robot Interaction with Computer Vision

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