Search Results for author:
Found 4 papers, 1 papers with code
CT-NeRF: Incremental Optimizing Neural Radiance Field and Poses with Complex Trajectory
In this pipeline, we first propose a local-global bundle adjustment under a pose graph connecting neighboring frames to enforce the consistency between poses to escape the local minima caused by only pose consistency with the scene structure.
Autonomous Implicit Indoor Scene Reconstruction with Frontier Exploration
In the paper, we propose to 1) incorporate frontier-based exploration tasks for global coverage with implicit surface uncertainty-based reconstruction tasks to achieve high-quality reconstruction.
Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields
With the popularity of implicit neural representations, or neural radiance fields (NeRF), there is a pressing need for editing methods to interact with the implicit 3D models for tasks like post-processing reconstructed scenes and 3D content creation.
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations
In this paper, we explore for the first time the possibility of using implicit neural representations for autonomous 3D scene reconstruction by addressing two key challenges: 1) seeking a criterion to measure the quality of the candidate viewpoints for the view planning based on the new representations, and 2) learning the criterion from data that can generalize to different scenes instead of a hand-crafting one.
