With the exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …

Objectives The shape is commonly used to describe the objects. State-of-the-art algorithms
in medical imaging are predominantly diverging from computer vision, where voxel grids …

Abstract Domain adaptation for 3D point cloud has attracted a lot of interest since it can
avoid the time-consuming labeling process of 3D data to some extent. A recent work named …

Unsupervised 2D image-based 3D shape retrieval aims to match the similar 3D unlabeled
shapes when given a 2D labeled sample. Although a lot of methods have made a certain …

Composed Query Based Image Retrieval (CQBIR) aims at searching images relevant to a
composed query, ie, a reference image together with a modifier text. Compared with …

Automatic anomaly detection based on visual cues holds practical significance in various
domains such as manufacturing and product quality assessment. This paper introduces a …

In recent years, 3D models have been utilized in many applications, such as auto-drivers,
3D reconstruction, VR, and AR. However, the scarcity of 3D model data does not meet its …

This paper studies the problem of semi-supervised 2D-3D retrieval which aims to align both
labeled and unlabeled 2D and 3D data into the same embedding space. The problem is …

The rise of the metaverse and the increasing volume of heterogeneous 2D and 3D data
have created a growing demand for cross-modal retrieval, enabling users to query …

Existing 2D image-based 3D model retrieval (IBMR) methods usually use the pseudo labels
as semantic guidance to reduce the domain-wise and class-wise feature distribution …