- Visual Features—From Early Concepts to Modern Computer Vision🔍
- Level Visual Feature🔍
- Visual Features & Tracking🔍
- Understanding Visual Feature Reliance through the Lens of ...🔍
- A systematic literature review of visual feature learning🔍
- Mapping the dynamics of visual feature coding🔍
- [2211.15060] Interactive Visual Feature Search🔍
- Prior object|knowledge sharpens properties of early visual feature ...🔍
Visual Feature
Visual Features—From Early Concepts to Modern Computer Vision
In this chapter, a definition of visual features is derived, and different types are presented which address both the spatial and the spatio-temporal domain.
Feature (computer vision) - Wikipedia
A feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties.
Level Visual Feature - an overview | ScienceDirect Topics
There are three main types of (low-level) visual features that have been applied: color-based features, texture-based features, and shape-based features.
Visual Features & Tracking: The fundamentals - Think Autonomous
Visual Features is something that is used in Computer Vision for object tracking, panoramic stitching, SLAM, 3D modeling, and many other ...
Understanding Visual Feature Reliance through the Lens of ... - arXiv
We introduce a new metric for quantifying feature complexity, based on \mathscr{V}-information and capturing whether a feature requires complex computational ...
A systematic literature review of visual feature learning
This systematic literature review aims to provide a comprehensive overview of the current state of visual feature learning techniques, applications, challenges ...
Mapping the dynamics of visual feature coding: Insights into ... - NCBI
This study highlights the importance of understanding how feature coding progresses through the visual hierarchy and the relationship between different stages ...
[2211.15060] Interactive Visual Feature Search - arXiv
Interactive visualizations allow users to more easily interpret a model's behavior, but most are not easily reusable for new models. We ...
Prior object-knowledge sharpens properties of early visual feature ...
We provide evidence from human vision that high-level object representations dynamically interact with the earliest stages of cortical visual processing.
Statistical learning of new visual feature combinations by infants
Infants learn higher-order visual features based on the statistical coherence of elements within the scenes, thereby allowing them to develop an efficient ...
Mapping the dynamics of visual feature coding: Insights into ... - PLOS
This study investigates the foundational computations in the human early visual cortex that underlie visual perception.
Visual feature integration and the temporal correlation hypothesis
Visual feature integration and the temporal correlation hypothesis.
Feature-based attention warps the perception of visual features
Selective attention improves sensory processing of relevant information but can also impact the quality of perception.
Visual Feature Learning on Video Object and Human Action Detection
In this paper, various video object and human action detection approaches are reviewed and discussed, many of them have performed state-of-the-art results.
Self-Supervised Visual Feature Learning With Deep Neural Networks
To avoid extensive cost of collecting and annotating large-scale datasets, as a subset of unsupervised learning methods, self-supervised ...
Visual Feature Tuning Properties of Short-Latency Stimulus-Driven ...
Results · The drift response exhibits size tuning · The drift response is stronger for high contrast stimuli · The drift response is ...
Parametric Instance Classification for Unsupervised Visual Feature ...
The code and network configurations are available at https://github.com/bl0/PIC. 1 Introduction. Visual feature learning has long been dominated by supervised ...
Using Visual Feature Space as a Pivot Across Languages
Our work aims to leverage visual feature space to pass information across languages. We show that models trained to generate textual captions in more than one ...
Visual feature-analyzers and aftereffects of tilt and curvature.
Explains the aftereffect produced by viewing a line tilted in the frontal plane in terms of the adaptation of orientation-specific units in the visual system.
Feature engineering is a key concept in machine learning describing the process of defining the characteristics of an observed phenomenon in a way that makes it ...