1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2023
IPVNet: Learning Implicit Point-Voxel Features for Open-Surface 3D Reconstruction
Mohammad Samiul Arshad, William J. Beksi
Reconstruction of 3D open surfaces (e.g., non-watertight meshes) is an underexplored area of computer vision. Recent learning-based implicit techniques have removed previous barrie…
cs.CV2023
LIST: Learning Implicitly from Spatial Transformers for Single-View 3D Reconstruction
Mohammad Samiul Arshad, William J. Beksi
Accurate reconstruction of both the geometric and topological details of a 3D object from a single 2D image embodies a fundamental challenge in computer vision. Existing explicit/i…
cs.CV2020★ 1 cited
A Progressive Conditional Generative Adversarial Network for Generating Dense and Colored 3D Point Clouds
Mohammad Samiul Arshad, William J. Beksi
In this paper, we introduce a novel conditional generative adversarial network that creates dense 3D point clouds, with color, for assorted classes of objects in an unsupervised ma…