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Toward Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
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Learning Spatial Context: Using Stuff to Find Things
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Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation
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Multiresolution Models for Object Detection
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A Generic Model to Compose Vision Modules for Holistic Scene Understanding
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A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants
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On the Design of Cascades of Boosted Ensembles for Face Detection
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3-D Depth Reconstruction from a Single Still Image
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Putting Objects in Perspective
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Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
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Contextual Priming for Object Detection
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Robust Real-Time Face Detection
inferredcites →https://doi.org/10.1037/0033-295x.113.4.766openalex-snapshot
Contextual guidance of eye movements and attention in real-world scenes: The role of global features in object search.
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Variational Gaussian process classifiers
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A Bayesian Hierarchical Model for Learning Natural Scene Categories
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Histograms of Oriented Gradients for Human Detection
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Monocular Human Motion Capture with a Mixture of Regressors
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Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
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Auto-context and its application to high-level vision tasks
inferredcites →https://doi.org/10.1109/cvpr.2008.4587587openalex-snapshot
Closing the loop in scene interpretation
inferredcites →https://doi.org/10.1109/cvpr.2008.4587595openalex-snapshot
From appearance to context-based recognition: Dense labeling in small images
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An empirical study of context in object detection
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Frequency-tuned salient region detection
inferredcites →https://doi.org/10.1109/cvpr.2009.5206718openalex-snapshot
Towards total scene understanding: Classification, annotation and segmentation in an automatic framework
inferredcites →https://doi.org/10.1109/cvpr.2010.5540114openalex-snapshot
Object detection via boundary structure segmentation
inferredcites →https://doi.org/10.1109/cvpr.2010.5540223openalex-snapshot
Multi-class object localization by combining local contextual interactions
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Modeling mutual context of object and human pose in human-object interaction activities
inferredcites →https://doi.org/10.1109/icassp.1993.319194openalex-snapshot
Cascaded neural networks based image classifier
inferredcites →https://doi.org/10.1109/iccv.2005.9openalex-snapshot
A hierarchical field framework for unified context-based classification
inferredcites →https://doi.org/10.1109/iccv.2007.4408872openalex-snapshot
What, where and who? Classifying events by scene and object recognition
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Discriminative models for multi-class object layout
inferredcites →https://doi.org/10.1109/iccv.2009.5459411openalex-snapshot
Recovering the spatial layout of cluttered rooms
inferredcites →https://doi.org/10.1109/icra.2011.5980177openalex-snapshot
FeCCM for scene understanding: Helping the robot to learn multiple tasks
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Depth estimation from image structure
inferredcites →https://doi.org/10.1109/tpami.2008.132openalex-snapshot
Make3D: Learning 3D Scene Structure from a Single Still Image
inferredcites →https://doi.org/10.1109/tpami.2009.167openalex-snapshot
Object Detection with Discriminatively Trained Part-Based Models
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Maximum Likelihood from Incomplete Data Via the EM Algorithm
inferredcites →https://doi.org/10.1145/1015330.1015341openalex-snapshot
Support vector machine learning for interdependent and structured output spaces
inferredcites →https://doi.org/10.1145/1390156.1390177openalex-snapshot
A unified architecture for natural language processing
inferredcites →https://doi.org/10.1145/1553374.1553523openalex-snapshot
Learning structural SVMs with latent variables
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A Fast Learning Algorithm for Deep Belief Nets
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Robotic Grasping of Novel Objects using Vision
inferredcites →https://doi.org/10.3115/1706543.1706587openalex-snapshot
Joint parsing and semantic role labeling
inferredcites →https://doi.org/10.5244/c.23.63openalex-snapshot
Object Localization with Global and Local Context Kernels
inferredcites →https://doi.org/10.5555/1046920.1194905openalex-snapshot
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
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Scaling Learning Algorithms toward AI
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Robotic Grasping of Novel Objects
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Sample Supervised Search‐Centric Approaches in Geographic Object‐Based Image Analysis
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Hallucinating Humans for Learning Robotic Placement of Objects
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PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding
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DEPT: Depth Estimation by Parameter Transfer for Single Still Images
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Depth Transfer: Depth Extraction from Videos Using Nonparametric Sampling
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Beyond the Line of Sight: Labeling the Underlying Surfaces
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Scalable scene understanding via saliency consensus
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Knowledge-driven understanding of images in comic books
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Labeling Complete Surfaces in Scene Understanding
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Semisupervised learning-based depth estimation with semantic inference guidance
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Context-based object viewpoint estimation: A 2D relational approach
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Depth estimation with convolutional conditional random field network
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Unsupervised Monocular Depth Reconstruction of Non-Rigid Scenes
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Learning the right model: Efficient max-margin learning in Laplacian CRFs
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Hallucinated Humans as the Hidden Context for Labeling 3D Scenes
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Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs
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Looking Beyond the Visible Scene
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Semi-Supervised Deep Learning for Monocular Depth Map Prediction
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Indoor/outdoor image classification using GIST image features and neural network classifiers
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Scalable scene understanding using saliency-guided object localization
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Image Segmentation with Cascaded Hierarchical Models and Logistic Disjunctive Normal Networks
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Intrinsic Depth: Improving Depth Transfer with Intrinsic Images
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DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding
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Iterative Action and Pose Recognition Using Global-and-Pose Features and Action-Specific Models
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Multi-level scene understanding via hierarchical classification
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Depth extraction from a single image by sampling based on distance metric learning
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Learning 3D structure from 2D images using LBP features
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Depth Transfer: Depth Extraction from Video Using Non-Parametric Sampling
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3D Reasoning from Blocks to Stability
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Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding
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Semantic Image Segmentation with Contextual Hierarchical Models
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Segmentation and indexation of complex objects in comic book images
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