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Found 5 papers, 0 papers with code
Non-parametric spatially constrained local prior for scene parsing on real-world data
Scene parsing aims to recognize the object category of every pixel in scene images, and it plays a central role in image content understanding and computer vision applications.
Spatially Constrained Location Prior for Scene Parsing
Semantic context is an important and useful cue for scene parsing in complicated natural images with a substantial amount of variations in objects and the environment.
Superpixel based Class-Semantic Texton Occurrences for Natural Roadside Vegetation Segmentation
In this paper, we present a novel approach that generates class-semantic color-texture textons and aggregates superpixel based texton occurrences for vegetation segmentation in natural roadside images.
Facial Expression Analysis under Partial Occlusion: A Survey
Automatic machine-based Facial Expression Analysis (FEA) has made substantial progress in the past few decades driven by its importance for applications in psychology, security, health, entertainment and human computer interaction.
Density Weighted Connectivity of Grass Pixels in Image Frames for Biomass Estimation
Accurate estimation of the biomass of roadside grasses plays a significant role in applications such as fire-prone region identification.
