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The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/11744078_24openalex-snapshot
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
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Learning a Sparse Representation for Object Detection
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Object class recognition by unsupervised scale-invariant learning
inferredcites →https://doi.org/10.1109/cvpr.2004.314openalex-snapshot
Combining Top-Down and Bottom-Up Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2005.288openalex-snapshot
Randomized Trees for Real-Time Keypoint Recognition
inferredcites →https://doi.org/10.1109/cvpr.2005.329openalex-snapshot
Spatial Priors for Part-Based Recognition Using Statistical Models
inferredcites →https://doi.org/10.1109/iccv.2001.937505openalex-snapshot
Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images
inferredcites →https://doi.org/10.1109/iccv.2003.1238478openalex-snapshot
Discriminative random fields: a discriminative framework for contextual interaction in classification
inferredcites →https://doi.org/10.1109/iccv.2005.148openalex-snapshot
LOCUS: learning object classes with unsupervised segmentation
inferredcites →https://doi.org/10.1109/iccv.2005.63openalex-snapshot
Contour-based learning for object detection
inferredcites →https://doi.org/10.1109/icdar.2005.151openalex-snapshot
Learning diagram parts with hidden random fields
inferredcites →https://doi.org/10.1109/tpami.2004.1262177openalex-snapshot
What energy functions can be minimized via graph cuts?
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Hierarchical and Networked Vehicle Surveillance in ITS: A Survey
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Fast Vehicle Detection Using a Disparity Projection Method
inferred← citeshttps://doi.org/10.1109/tnnls.2021.3124580openalex-snapshot
Event-Based Motion Segmentation With Spatio-Temporal Graph Cuts
inferred← citeshttps://doi.org/10.1109/tpami.2007.70772openalex-snapshot
Multiscale Categorical Object Recognition Using Contour Fragments
inferred← citeshttps://doi.org/10.1109/tpami.2007.70840openalex-snapshot
Combined Top-Down/Bottom-Up Segmentation
inferred← citeshttps://doi.org/10.1109/tpami.2009.120openalex-snapshot
Order-Preserving Moves for Graph-Cut-Based Optimization
inferred← citeshttps://doi.org/10.1109/tpami.2009.131openalex-snapshot
Global Stereo Reconstruction under Second-Order Smoothness Priors
inferred← citeshttps://doi.org/10.1109/tpami.2009.143openalex-snapshot
Fusion Moves for Markov Random Field Optimization
inferred← citeshttps://doi.org/10.1109/tpami.2009.145openalex-snapshot
Image Segmentation with a Unified Graphical Model
inferred← citeshttps://doi.org/10.1109/tpami.2009.16openalex-snapshot
OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues
inferred← citeshttps://doi.org/10.1109/tpami.2009.204openalex-snapshot
Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching
inferred← citeshttps://doi.org/10.1109/tpami.2011.208openalex-snapshot
Layered Object Models for Image Segmentation
inferred← citeshttps://doi.org/10.1109/tpami.2011.43openalex-snapshot
Layered Graphical Models for Tracking Partially Occluded Objects
inferred← citeshttps://doi.org/10.1109/tpami.2011.70openalex-snapshot
Hough Forests for Object Detection, Tracking, and Action Recognition
inferred← citeshttps://doi.org/10.1109/tpami.2012.174openalex-snapshot
Monocular Visual Scene Understanding: Understanding Multi-Object Traffic Scenes
inferred← citeshttps://doi.org/10.1109/tpami.2012.194openalex-snapshot
Hough Forest Random Field for Object Recognition and Segmentation
inferred← citeshttps://doi.org/10.1109/tpami.2012.241openalex-snapshot
Efficient Human Pose Estimation from Single Depth Images
inferred← citeshttps://doi.org/10.1109/tpami.2013.193openalex-snapshot
Relating Things and Stuff via ObjectProperty Interactions
inferred← citeshttps://doi.org/10.1109/tpami.2016.2547399openalex-snapshot
Convexity Shape Prior for Binary Segmentation
inferred← citeshttps://doi.org/10.1109/tpami.2017.2708714openalex-snapshot
Exploring Context with Deep Structured Models for Semantic Segmentation
inferred← citeshttps://doi.org/10.1109/tpami.2022.3150906openalex-snapshot
ROAD: The Road Event Awareness Dataset for Autonomous Driving
inferred← citeshttps://doi.org/10.1109/tpami.2023.3246174openalex-snapshot
Occlusion-Aware Instance Segmentation Via BiLayer Network Architectures
inferred← citeshttps://doi.org/10.1109/wacvw.2016.7470122openalex-snapshot
Detecting plains and Grevy's Zebras in the realworld
inferred← citeshttps://doi.org/10.1109/wcica.2010.5554343openalex-snapshot
Object detection and segmentation based on shape learning and Dynamic Bayesian network
inferred← citeshttps://doi.org/10.1117/12.2038707openalex-snapshot
Investigation of segmentation based pooling for image quantification
inferred← citeshttps://doi.org/10.1117/12.2077175openalex-snapshot
Detection and handling of occlusion in an object detection system
inferred← citeshttps://doi.org/10.1117/12.899294openalex-snapshot
Fusion of hyperspectral and lidar data using morphological attribute profiles
inferred← citeshttps://doi.org/10.1145/1390156.1390203openalex-snapshot
Boosting with incomplete information
inferred← citeshttps://doi.org/10.1145/1924559.1924598openalex-snapshot
An indexing approach for speeding-up image classification
inferred← citeshttps://doi.org/10.1145/2398356.2398381openalex-snapshot
Real-time human pose recognition in parts from single depth images
inferred← citeshttps://doi.org/10.1145/3230519.3230593openalex-snapshot
A multi-task learning approach for meal assessment
inferred← citeshttps://doi.org/10.1145/3465629openalex-snapshot
Deep Segmentation of Corrupted Glyphs
inferred← citeshttps://doi.org/10.1155/2011/101428openalex-snapshot
Robust Object Categorization and Segmentation Motivated by Visual Contexts in the Human Visual System
inferred← citeshttps://doi.org/10.11606/t.3.2009.tde-01072009-153749openalex-snapshot
Construção de mapas de objetos para navegação de robôs.
inferred← citeshttps://doi.org/10.14288/1.0051537openalex-snapshot
New probabilistic inference algorithms that harness the strengths of variational and Monte Carlo methods
inferred← citeshttps://doi.org/10.15607/rss.2008.iv.008openalex-snapshot
Prior Data and Kernel Conditional Random Fields for Obstacle Detection
inferred← citeshttps://doi.org/10.1561/0600000095openalex-snapshot
Semantic Image Segmentation: Two Decades of Research
inferred← citeshttps://doi.org/10.1587/transinf.e95.d.835openalex-snapshot
View-Based Object Recognition Using ND Tensor Supervised Neighborhood Embedding
inferred← citeshttps://doi.org/10.1609/aaai.v35i4.16407openalex-snapshot
Amodal Segmentation Based on Visible Region Segmentation and Shape Prior
inferred← citeshttps://doi.org/10.1609/aaai.v37i1.25104openalex-snapshot
Amodal Instance Segmentation via Prior-Guided Expansion
inferred← citeshttps://doi.org/10.18178/ijmlc.2017.7.6.652openalex-snapshot
Removing Shadows from Video
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