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CLIP-Forge: Towards Zero-Shot Text-To-Shape Generation
Generating shapes using natural language can enable new ways of imagining and creating the things around us. While significant recent …
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CLIP-Forge: Towards Zero-Shot Text-To-Shape Generation
GIM3D: A 3D Dataset for Garment Segmentation
The 3D cloth segmentation task is particularly challenging due to the extreme variation of shapes, even among the same category of …
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GIM3D: A 3D Dataset for Garment Segmentation
Neural Implicit Style-net: synthesizing shapes in a preferred style exploiting self supervision
We introduce a novel approach to disentangle style from content in the 3D domain and perform unsupervised neural style transfer. Our …
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Neural Implicit Style-net: synthesizing shapes in a preferred style exploiting self supervision
PC-GAU: PCA Basis of Scattered Gaussians for Shape Matching via Functional Maps
Shape matching is a central problem in geometry processing applications, ranging from texture transfer to statistical shape analysis. …
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PC-GAU: PCA Basis of Scattered Gaussians for Shape Matching via Functional Maps
Multitask Prompted Training Enables Zero-Shot Task Generalization
Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., …
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Multitask Prompted Training Enables Zero-Shot Task Generalization
Learning disentangled representations via product manifold projection
We propose a novel approach to disentangle the generative factors of variation underlying a given set of observations. Our method …
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Learning disentangled representations via product manifold projection
Shape registration in the time of transformers
In this paper, we propose a transformer-based procedure for the efficient registration of non-rigid 3D point clouds. The proposed …
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Shape registration in the time of transformers
Cluster-driven Graph Federated Learning over Multiple Domains
Federated Learning (FL) deals with learning a central model (i.e. the server) in privacy-constrained scenarios, where data are stored …
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Cluster-driven Graph Federated Learning over Multiple Domains
Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence With Functional Maps
In this paper, we provide a theoretical foundation for pointwise map recovery from functional maps and highlight its relation to a …
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Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence With Functional Maps
Universal Spectral Adversarial Attacks for Deformable Shapes
Machine learning models are known to be vulnerable to adversarial attacks, namely perturbations of the data that lead to wrong …
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Universal Spectral Adversarial Attacks for Deformable Shapes