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Global contrast based salient region detection
TLDR
This work proposes a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence, and consistently outperformed existing saliency detection methods.
View on IEEE
4-points congruent sets for robust pairwise surface registration
TLDR
4PCS, a fast and robust alignment scheme for 3D point sets that uses wide bases, which are known to be resilient to noise and outliers, is introduced and an extension to handle similarity and affine transforms is proposed.
View on ACM
Super 4PCS Fast Global Pointcloud Registration via Smart Indexing
TLDR
This work presents Super 4PCS for global pointcloud registration that is optimal, i.e., runs in linear time and is also output sensitive in the complexity of the alignment problem based on the (unknown) overlap across scan pairs.
View on Wiley
Robust global registration
TLDR
This work presents an algorithm for the automatic alignment of two 3D shapes ( data and model), without any assumptions about their initial positions, and develops a fast branch-and-bound algorithm based on distance matrix comparisons to select the optimal correspondence set and bring the two shapes into a coarse alignment.
View on ACM
PCPNet Learning Local Shape Properties from Raw Point Clouds
TLDR
The utility of the PCPNET approach in the context of shape reconstruction is demonstrated, by showing how it can be used to extract normal orientation information from point clouds.
View on Wiley
SalientShape: group saliency in image collections
TLDR
This work introduces group saliency to achieve superior unsupervised salient object segmentation by extracting salient objects (in collections of pre-filtered images) that maximize between-image similarities and within-image distinctness.
View on Springer
StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows
TLDR
This article presents StyleFlow as a simple, effective, and robust solution to both the sub-problems of attribute-conditioned sampling and attribute-controlled editing by formulating conditional exploration as an instance of conditional continuous normalizing flows in the GAN latent space conditioned by attribute features.
View on ACM
Partial and approximate symmetry detection for 3D geometry
TLDR
A new algorithm is presented that processes geometric models and efficiently discovers and extracts a compact representation of their Euclidean symmetries, which captures important high-level information about the structure of a geometric model which enables a large set of further processing operations.
View on ACM
Geometric modeling in shape space
We present a novel framework to treat shapes in the setting of Riemannian geometry. Shapes -- triangular meshes or more generally straight line graphs in Euclidean space -- are treated as points in a…
View on ACM
PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds
TLDR
This work develops a simple data‐driven method for removing outliers and reducing noise in unordered point clouds using a deep learning architecture adapted from PCPNet, which was recently proposed for estimating local 3D shape properties in point clouds.
View on Wiley
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