Perception(10)
* Cortical Anatomy, Size Invariance, and Spatial Frequency Analysis
* Size Invariance: Reply to Schwartz
Perception(11)
* Shape of Smooth Objects and the Way Contours End, The
Perception(13)
* Maximizing Rigidity: The Incremental Recovery of 3-D Structure from Rigidity and Rubbery Motion
* What Does the Occluding Contour Tell Us About Solid Shape?
Perception(14)
* PMF: A Stereo Correspondence Algorithm Using a Disparity Gradient Limit
Perception(24)
* Is Object Recognition Mediated by Viewpoint Invariant Parts or Viewpoint Dependent Features
* To What Extent Do Unique Parts Influence Recognition Across Changes in Viewpoint
Perception(25)
* Perturbation study of shading in pictures
* Shape Constancy in Pictorial Relief
Perception(26)
* Steering without Representation using Active Fixation
Perception(30)
* Computational and performance aspects of PCA-based face recognition algorithms
Perception(5)
* Optical Flow Field: The Foundation of Vision, The
Perception(7)
* Size and Position Invariance in the Visual System
Perception(8)
* On the Limits of Fourier Decompositions in Visual Texture Perception
Perception(9)
* Perception of Surface Slant and Edge Labels from Optical Flow: A Computational Approach
PerceptualRest18
* *Perceptual Image Restoration and Manipulation Workshop and Challenge
* 2018 PIRM Challenge on Perceptual Image Super-Resolution, The
* AI Benchmark: Running Deep Neural Networks on Android Smartphones
* Analyzing Perception-Distortion Tradeoff Using Enhanced Perceptual Super-Resolution Network
* Bi-GANs-ST for Perceptual Image Super-Resolution
* CARN: Convolutional Anchored Regression Network for Fast and Accurate Single Image Super-Resolution
* Deep Networks for Image-to-Image Translation with Mux and Demux Layers
* Deep Residual Attention Network for Spectral Image Super-Resolution
* ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
* Fast and Efficient Image Quality Enhancement via Desubpixel Convolutional Neural Networks
* Fast Perceptual Image Enhancement
* Generative Adversarial Network-Based Image Super-Resolution Using Perceptual Content Losses
* Multi-modal Spectral Image Super-Resolution
* Multi-scale Recursive and Perception-Distortion Controllable Image Super-Resolution
* Multiple Connected Residual Network for Image Enhancement on Smartphones
* Perception-Enhanced Image Super-Resolution via Relativistic Generative Adversarial Networks
* Perception-Preserving Convolutional Networks for Image Enhancement on Smartphones
* PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
* PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study
* PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results
* Range Scaling Global U-Net for Perceptual Image Enhancement on Mobile Devices
* Scale-Recurrent Multi-residual Dense Network for Image Super-Resolution
* Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution, The
23 for PerceptualRest18
PerComp
* *IEEE Pervasive Computing
PerComp(10)
* Facial Expression Analysis for Predicting Unsafe Driving Behavior
PerComp(4)
* Computerized real-time analysis of football games
PercOrg01
* *Workshop on Perceptual Organization in Computer Vision
* Analysis of MinCut, Average Cut, and Normalized Cut Measures
* Color Image Segmentation Based on Tensor Voting
* Conceptualization and Modeling of Visual Patterns
* Contour Grouping with Strong Prior Models
* Convex Relaxation for Figure-Ground Discrimination and Perceptual Grouping
* Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms, A
* Expectation-Maximisation Framework for Segmentation and Grouping, An
* Field Model for Contour Organization and Partial Differential Equations, A
* Finding Perceptually Closed Paths in Sketches and Drawings
* Flowing toward coherence: On the geometry of texture and shading flows
* Grouping Using Regions: A Consistency Study
* Guest editors' introduction to the special section on perceptual organization in computer vision
* Inference of Segmented Overlapping Surfaces from Binocular and Multiple-View Stereo
* Integrated Tensor Voting in Multiple Scales for Shape Description in 3D
* Perceptual Grouping by Path Based Clustering
* Perceptual Grouping for Image Retrieval and Classification
* Perceptual organization as graph rectification in a constraint-based scheme for interpreting sloppy stick figures
* Perceptual Organization as Object Recognition Divided by Two
* Towards Statistical Image Restoration: Perceptual Grouping as Regularizing Operators
* Understanding Gestalt Cues and Ecological Statistics Using A Database of Human Segmented Images
21 for PercOrg01
PercOrg04
* *Workshop on Perceptual Organization in Computer Vision
* Accurate Automatic Localization of Surfaces of Revolution for Self-Calibration and Metric Reconstruction
* Automatic Single View Building Reconstruction by Integrating Segmentation
* Bayesian Network Framework for Real-Time Object Selection, A
* Challenges in Segmentation of Human Forms in Outdoor Video
* Combining Top-Down and Bottom-Up Segmentation
* Efficient Computation of Closed Contours using Modified Baum-Welch Updating
* Embodied Approach to Perceptual Grouping, An
* Fitting Superellipses to Incomplete Contours
* Graph Partitioning Active Contours for Knowledge-Based Geo-Spatial Segmentation
* Junction Inference and Classification for Figure Completion using Tensor Voting
* Learning a Probabilistic Similarity Function for Segmentation
* Learning Perceptual Organization with a Developmental Robot
* Matching and Interpretation of Planar Motion Using Tensor Voting
* Maximum Response Filters for Texture Analysis
* Medial Visual Fragments as an Intermediate Image Representation for Segmentation and Perceptual Grouping
* Normalized Texture Motifs and Their Application to Statistical Object Modeling
* Overview of the 2004 Workshop on Perceptual Organization in Computer Vision, An
* Threshold Selection as a Function of Region Count Stability
* Towards Perceptually Driven Segmentation Evaluation Metrics
20 for PercOrg04
PercOrg06
* *Workshop on Perceptual Organization in Computer Vision
* Audiovisual Gestalts
* Background Initialization in Cluttered Sequences
* Boundary Extraction in Natural Images Using Ultrametric Contour Maps
* Combinatorial Grouping of Edges using Geometric Consistency in a Lagrangian Framework
* Consistency of location and gradient judgments of visually-interpolated contours
* Contour extrapolation using probabilistic cue combination
* Detecting Bilateral Symmetry in Perspective
* Fast and Adaptive Pairwise Similarities for Graph Cuts-based Image Segmentation
* Finding Minimal Parameterizations of Cylindrical Image Manifolds
* Framework for Evaluating Video Object Segmentation Algorithms, A
* Gabor Filter Analysis for Texture Segmentation
* Globally Optimal Interactive Boundary Extraction Using Markov Chain Modeling
* Good Continuation in Layers: Shading flows, color flows, surfaces and shadows
* Learning Association Fields from Natural Images
* Learning Top-Down Grouping of Compositional Hierarchies for Recognition
* Min-Cover Approach for Finding Salient Curves, A
* Motion Segmentation by Spatiotemporal Smoothness Using 5D Tensor Voting
* Moving Object Segmentation using Scene Understanding
* Multi-modal Scene Reconstruction using Perceptual Grouping Constraints
* Multi-Scale Contour Extraction Based on Natural Image Statistics
* Multiscale Modeling and Constraints for Max-flow/Min-cut Problems in Computer Vision
* Mutual Segmentation with Level Sets
* Object Recognition Using a Generalized Robust Invariant Feature and Gestalt's Law of Proximity and Similarity
* Perceptual Information of Images and the Bias in Homogeneity-based Segmentation
* Robust Boundary Detection With Adaptive Grouping
* Saliency and Segregation Without Feature Gradient: New Insights for Segmentation from Orientation-Defined Textures
* Salient Contour Detection using a Global Contour Discontinuity Measurement
* Synergy in the multi-local statistics of gradient directions in images
* Transitivity-based Removal of Correspondence Outliers for Motion Analysis
* Tree Trunks as Landmarks for Outdoor Vision SLAM
31 for PercOrg06