IFKD: Implicit field knowledge distillation for single view reconstruction.

In 3D reconstruction tasks, camera parameter matrix estimation is usually used to present the single view of an object, which is not necessary when mapping the 3D point to 2D image. The single view reconstruction task should care more about the quality of reconstruction instead of the alignment. So in this paper, we propose an implicit field knowledge distillation model (IFKD) to reconstruct 3D objects from the single view.

Adaptive Points Sampling for Implicit Field Reconstruction of Industrial Digital Twin.

Nowadays, the digital twin (DT) plays an important role in Industry 4.0. It aims to model reality in the digital space for further industrial maintenance, management, and optimization.

Improved Panoramic Representation via Bidirectional Recurrent View Aggregation for Three-Dimensional Model Retrieval.

In a view-based three-dimensional (3-D) model retrieval task, extracting discriminative high-level features of models from projected images is considered as an effective approach. The challenge of view-based 3-D shape retrieval is that the shape information of each view is limited due to information deficiency in projection. Traditional methods in this direction mostly convert the model into a panoramic view, making it hard to recognize the original shape.

Learning Discriminative 3D Shape Representations by View Discerning Networks.

In view-based 3D shape recognition, extracting discriminative visual representation of 3D shapes from projected images is considered the core problem. Projections with low discriminative ability can adversely influence the final 3D shape representation. Especially under the real situations with background clutter and object occlusion, the adverse effect is even more severe.

Dimensionality Reduction in Multiple Ordinal Regression.

Supervised dimensionality reduction (DR) plays an important role in learning systems with high-dimensional data. It projects the data into a low-dimensional subspace and keeps the projected data distinguishable in different classes. In addition to preserving the discriminant information for binary or multiple classes, some real-world applications also require keeping the preference degrees of assigning the data to multiple aspects, e.

3D object retrieval with multitopic model combining relevance feedback and LDA model.

View-based 3D model retrieval uses a set of views to represent each object. Discovering the complex relationship between multiple views remains challenging in 3D object retrieval. Recent progress in the latent Dirichlet allocation (LDA) model leads us to propose its use for 3D object retrieval.