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Found 15 papers, 0 papers with code
Achieving Rotation Invariance in Convolution Operations: Shifting from Data-Driven to Mechanism-Assured
Based on various types of non-learnable operators, including gradient, sort, local binary pattern, maximum, etc., this paper designs a set of new convolution operations that are natually invariant to arbitrary rotations.
Sorted Convolutional Network for Achieving Continuous Rotational Invariance
The topic of achieving rotational invariance in convolutional neural networks (CNNs) has gained considerable attention recently, as this invariance is crucial for many computer vision tasks such as image classification and matching.
Image Moment Invariants to Rotational Motion Blur
Further, we achieve their invariance to similarity transform.
RIC-CNN: Rotation-Invariant Coordinate Convolutional Neural Network
Using MNIST dataset, we first evaluate the rotation invariance of RIC-CNN and compare its performance with most of existing rotation-invariant CNN models.
Gaussian-Hermite Moment Invariants of General Multi-Channel Functions
Then, we design a structural framework to generate Gaussian-Hermite moment invariants for these two transform models systematically.
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition
The dynamics of human skeletons have significant information for the task of action recognition.
Dual affine moment invariants
In this paper, we propose a general framework to derive moment invariants under DAT for objects in M-dimensional space with N channels, which can be called dual-affine moment invariants (DAMI).
Rotation Differential Invariants of Images Generated by Two Fundamental Differential Operators
As far as we know, no previous papers have published so many explicit forms of high-order rotation differential invariants of images.
Differential and integral invariants under Mobius transformation
According to the Liouville Theorem, an important part of the conformal transformation is the Mobius transformation, so we focus on Mobius transformation and propose two differential expressions that are invariable under 2-D and 3-D Mobius transformation respectively.
Fast and Efficient Calculations of Structural Invariants of Chirality
And the five chiral invariants have four characteristics:(1) They play an important role in the detection of symmetry, especially in the treatment of 'false zero' problem.
Image Projective Invariants
In this paper, we propose relative projective differential invariants (RPDIs) which are invariant to general projective transformations.
Shape-Color Differential Moment Invariants under Affine Transformations
We propose the general construction formula of shape-color primitives by using partial differentials of each color channel in this paper.
A Kind of Affine Weighted Moment Invariants
A new kind of geometric invariants is proposed in this paper, which is called affine weighted moment invariant (AWMI).
Naturally Combined Shape-Color Moment Invariants under Affine Transformations
We proposed a kind of naturally combined shape-color affine moment invariants (SCAMI), which consider both shape and color affine transformations simultaneously in one single system.
Affine-Gradient Based Local Binary Pattern Descriptor for Texture Classiffication
We present a novel Affine-Gradient based Local Binary Pattern (AGLBP) descriptor for texture classification.
