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KERMIT: Complementing Transformer Architectures with Encoders of Explicit Syntactic Interpretations
Syntactic parsers have dominated natural language understanding for decades. Yet, their syntactic interpretations are losing centrality …
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KERMIT: Complementing Transformer Architectures with Encoders of Explicit Syntactic Interpretations
LIMP: Learning Latent Shape Representations with Metric Preservation Priors
In this paper, we advocate the adoption of metric preservation as a powerful prior for learning latent representations of deformable 3D …
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LIMP: Learning Latent Shape Representations with Metric Preservation Priors
Learning interaction patterns from surface representations of protein structure
Predicting interactions between proteins and other biomolecules purely based on structure is an unsolved problem in biology. The …
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Learning interaction patterns from surface representations of protein structure
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment
We consider the problem of localizing relevant subsets of non-rigid geometric shapes given only a partial 3D query as the input. Such …
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Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment
High-Resolution Augmentation for Automatic Template-Based Matching of Human Models
We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three …
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High-Resolution Augmentation for Automatic Template-Based Matching of Human Models
GFrames: Gradient-based local reference frame for 3D shape matching
We introduce GFrames, a novel local reference frame (LRF) construction for 3D meshes and point clouds. GFrames are based on the …
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GFrames: Gradient-based local reference frame for 3D shape matching
Unsupervised learning of dense shape correspondence
We introduce the first completely unsupervised correspondence learning approach for deformable 3D shapes. Key to our model is the …
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Unsupervised learning of dense shape correspondence
SHREC'19: Matching humans with different connectivity
Objects Matching is a ubiquitous problem in computer science with particular relevance for many applications; property transfer between …
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SHREC'19: Matching humans with different connectivity
SHREC'19: Shape Correspondence with Isometric and Non-Isometric Deformations
The registration of non-rigidly deforming shapes is a fundamental problem in the area of Graphics and Computational Geometry. One of …
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SHREC'19: Shape Correspondence with Isometric and Non-Isometric Deformations
Isospectralization, or how to hear shape, style, and correspondence
The question whether one can recover the shape of a geometric object from its Laplacian spectrum (‘hear the shape of the …
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Isospectralization, or how to hear shape, style, and correspondence