Fitness landscape analysis is a data-driven technique to study the relationship between
problem characteristics and algorithm performance by characterizing the landscape features …

In this paper, we propose IPD-Net: Invariant Primitive Decompositional Network, a SO (3)
invariant framework for decomposition of a point cloud. The human cognitive system is able …

Abstract In southeastern North America, Indigenous potters and woodworkers carved
complex, primarily abstract, designs into wooden pottery paddles, which were subsequently …

3D surface matching by local feature descriptors is a fundamental task in 3D object
registration, recognition, and retrieval. In view of 2D projected descriptors' information …

In recent years, computer vision research has focused on extracting features from 3D data.
In this work, we reviewed methods of extracting local features from objects represented in …

Deep learning's shift from supervised to unsupervised methods has revolutionized many
applications, exemplified by innovations such as DALL-E-2 and Chat-GPT. This paper …

In this paper, a critical points based descriptor for 3 D objects recognition is presented. It is
based on the topological invariant provided by the critical points of the 3 D object. The …

Binary descriptors have been widely used for real-time image retrieval and correspondence
matching. However, most of the learned descriptors are obtained using a large deep neural …

This article presents a method for the description of key points using simple statistics for
regions controlled by neighboring key points to remedy the gap in existing descriptors …

Nowadays, with easily accessible 3D point cloud acquisition tools, the field of point cloud
processing gained a lot of attention. Extracting features from 3D data became main …