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Found 6 papers, 5 papers with code
Visual Localization via Few-Shot Scene Region Classification
Visual (re)localization addresses the problem of estimating the 6-DoF (Degree of Freedom) camera pose of a query image captured in a known scene, which is a key building block of many computer vision and robotics applications.
A Simple And Effective Filtering Scheme For Improving Neural Fields
Our solution is a new filtering technique that consists of two counteractive operators: a smoothing operator that provides global smoothing for better generalization, and conversely a recovering operator that provides better controllability for local adjustments.
Neural Implicit 3D Shapes from Single Images with Spatial Patterns
However, the image features for describing 3D point samplings of implicit functions are less effective when significant variations of occlusions, views, and appearances exist from the image.
Multimodal Shape Completion via Conditional Generative Adversarial Networks
Several deep learning methods have been proposed for completing partial data from shape acquisition setups, i. e., filling the regions that were missing in the shape.
Decoupling Features and Coordinates for Few-shot RGB Relocalization
To address this issue, we approach camera relocalization with a decoupled solution where feature extraction, coordinate regression, and pose estimation are performed separately.
PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes
We introduce PQ-NET, a deep neural network which represents and generates 3D shapes via sequential part assembly.
