Review of multi-view 3D object recognition methods based on deep learning
Abstract Three-dimensional (3D) object recognition is widely used in automated driving,
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
[HTML][HTML] DILF: Differentiable rendering-based multi-view Image–Language Fusion for zero-shot 3D shape understanding
Zero-shot 3D shape understanding aims to recognize “unseen” 3D categories that are not
present in training data. Recently, Contrastive Language–Image Pre-training (CLIP) has …
present in training data. Recently, Contrastive Language–Image Pre-training (CLIP) has …
Deep learning for 3D object recognition: A survey
With the growing availability of extensive 3D datasets and the rapid progress in
computational power, deep learning (DL) has emerged as a highly promising approach for …
computational power, deep learning (DL) has emerged as a highly promising approach for …
Mv-reid: 3d multi-view transformation network for occluded person re-identification
Re-identification (ReID) of occluded persons is a challenging task due to the loss of
information in scenes with occlusions. Most existing methods for occluded ReID use 2D …
information in scenes with occlusions. Most existing methods for occluded ReID use 2D …
[PDF][PDF] Intelligent deep learning and improved whale optimization algorithm based framework for object recognition
In pattern recognition, object recognition is an important research domain due to major
applications such as autonomous driving, robotics, and visual surveillance. Many computer …
applications such as autonomous driving, robotics, and visual surveillance. Many computer …
Cross-lingual cross-modal retrieval with noise-robust learning
Despite the recent developments in the field of cross-modal retrieval, there has been less
research focusing on low-resource languages due to the lack of manually annotated …
research focusing on low-resource languages due to the lack of manually annotated …
Fine-grained fashion similarity prediction by attribute-specific embedding learning
This paper strives to predict fine-grained fashion similarity. In this similarity paradigm, one
should pay more attention to the similarity in terms of a specific design/attribute between …
should pay more attention to the similarity in terms of a specific design/attribute between …
RGAM: A novel network architecture for 3D point cloud semantic segmentation in indoor scenes
XT Chen, Y Li, JH Fan, R Wang - Information Sciences, 2021 - Elsevier
Abstract Three-dimensional (3D) point cloud semantic segmentation is an essential part of
computer vision for scene comprehension. Nevertheless, due to their loss of detail, existing …
computer vision for scene comprehension. Nevertheless, due to their loss of detail, existing …
Multi-view 3D object retrieval leveraging the aggregation of view and instance attentive features
In multi-view 3D object retrieval tasks, it is pivotal to aggregate visual features extracted from
multiple view images to generate a discriminative representation for a 3D object. The …
multiple view images to generate a discriminative representation for a 3D object. The …
A clustering-guided contrastive fusion for multi-view representation learning
Multi-view representation learning aims to extract comprehensive information from multiple
sources. It has achieved significant success in applications such as video understanding …
sources. It has achieved significant success in applications such as video understanding …