Search Results for author:
Found 4 papers, 2 papers with code
Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentation
To address these limitations, we propose a novel approach that leverages the newly proposed Adaptive Implicit Representation Mapping (AIRM) for ultra-high-resolution Image Segmentation.
Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal
State-of-the-art shadow removal methods train deep neural networks on collected shadow & shadow-free image pairs, which are desired to complete two distinct tasks via shared weights, i. e., data restoration for shadow regions and identical mapping for non-shadow regions.
Orthogonal Dictionary Guided Shape Completion Network for Point Cloud
Point cloud shape completion, which aims to reconstruct the missing regions of the incomplete point clouds with plausible shapes, is an ill-posed and challenging task that benefits many downstream 3D applications.
Ranked #1 on
Point Cloud Completion
on ShapeNet
Parametric Surface Constrained Upsampler Network for Point Cloud
Designing a point cloud upsampler, which aims to generate a clean and dense point cloud given a sparse point representation, is a fundamental and challenging problem in computer vision.
Ranked #3 on
Point Cloud Completion
on ShapeNet
