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Superpixels

Superpixel techniques segment an image into regions based on similarity measures that utilize perceptual features, effectively grouping pixels that appear similar. The motivation behind this approach is to generate regions that provide meaningful descriptions while significantly reducing the data volume compared to using every individual pixel. By decreasing the number of primitives, these techniques reduce redundancy and simplify the complexity of recognition tasks. Superpixels replace the rigid structure of individual pixels with delineated regions that preserve meaningful content in the image, thereby aiding the interpretation of the scene’s structure and simplifying subsequent processing tasks. Generally, superpixel techniques rely on measures that evaluate color similarities and the shapes of regions, incorporating edges or significant changes in intensity to define these regions.

Papers

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Showing 301–350 of 371 papers

TitleStatusHype
Leave-One-Out Kernel Optimization for Shadow Detection—0
Efficient Classifier Training to Minimize False Merges in Electron Microscopy Segmentation—0
Semantic Component Analysis—0
Higher Order Conditional Random Fields in Deep Neural NetworksCode0
Superpixel Convolutional Networks using Bilateral InceptionsCode0
Structured Depth Prediction in Challenging Monocular Video Sequences—0
Moral Lineage Tracing—0
Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering—0
Image Parsing with a Wide Range of Classes and Scene-Level Context—0
gSLICr: SLIC superpixels at over 250HzCode0
Action recognition in still images by latent superpixel classification—0
Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation—0
Natural Scene Recognition Based on Superpixels and Deep Boltzmann Machines—0
DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation—0
Learning to Segment Object CandidatesCode0
Tree-Cut for Probabilistic Image Segmentation—0
Single Target Tracking Using Adaptive Clustered Decision Trees and Dynamic Multi-Level Appearance Models—0
Superpixel Meshes for Fast Edge-Preserving Surface Reconstruction—0
Superpixel Segmentation Using Linear Spectral Clustering—0
Complexity-Adaptive Distance Metric for Object Proposals Generation—0
Real-Time Coarse-to-Fine Topologically Preserving Segmentation—0
Classifier Based Graph Construction for Video Segmentation—0
Object Detection by Labeling Superpixels—0
Object Scene Flow for Autonomous Vehicles—0
A Weighted Sparse Coding Framework for Saliency Detection—0
Inner and Inter Label Propagation: Salient Object Detection in the WildCode0
Image Segmentation Using Hierarchical Merge TreeCode0
A Bottom-up Approach for Pancreas Segmentation using Cascaded Superpixels and (Deep) Image Patch Labeling—0
Deep convolutional networks for pancreas segmentation in CT imaging—0
CRF Learning with CNN Features for Image Segmentation—0
Superpixelizing Binary MRF for Image Labeling Problems—0
Boosting Convolutional Features for Robust Object Proposals—0
What Properties are Desirable from an Electron Microscopy Segmentation Algorithm—0
Data-Driven Scene Understanding with Adaptively Retrieved Exemplars—0
Weakly Supervised Learning for Salient Object Detection—0
Unsupervised image segmentation by Global and local Criteria Optimization Based on Bayesian Networks—0
What is a salient object? A dataset and a baseline model for salient object detection—0
Feedforward semantic segmentation with zoom-out featuresCode0
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional ArchitectureCode0
Deep Deconvolutional Networks for Scene Parsing—0
Visual Chunking: A List Prediction Framework for Region-Based Object Detection—0
A Bottom-Up Approach for Automatic Pancreas Segmentation in Abdominal CT Scans—0
A Statistical Modeling Approach to Computer-Aided Quantification of Dental Biofilm—0
A Context-aware Delayed Agglomeration Framework for Electron Microscopy SegmentationCode0
Learning Optimal Seeds for Diffusion-based Salient Object Detection—0
Fast, Approximate Piecewise-Planar Modeling Based on Sparse Structure-from-Motion and Superpixels—0
Tell Me What You See and I will Show You Where It Is—0
Single-View 3D Scene Parsing by Attributed Grammar—0
Spectral Graph Reduction for Efficient Image and Streaming Video Segmentation—0
Generating Object Segmentation Proposals using Global and Local Search—0
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