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04/27/2023
ClusterNet: A Perception-Based Clustering Model for Scattered Data
Cluster separation in scatterplots is a task that is typically tackled b...
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10/11/2022
Weakly-Supervised Optical Flow Estimation for Time-of-Flight
Indirect Time-of-Flight (iToF) cameras are a widespread type of 3D senso...
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05/31/2022
Contrastive Representation Learning for 3D Protein Structures
Learning from 3D protein structures has gained wide interest in protein ...
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03/29/2022
Clean Implicit 3D Structure from Noisy 2D STEM Images
Scanning Transmission Electron Microscopes (STEMs) acquire 2D images of ...
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02/18/2022
Gaussian Mixture Convolution Networks
This paper proposes a novel method for deep learning based on the analyt...
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12/07/2021
Variance-Aware Weight Initialization for Point Convolutional Neural Networks
Appropriate weight initialization has been of key importance to successf...
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11/30/2021
RADU: Ray-Aligned Depth Update Convolutions for ToF Data Denoising
Time-of-Flight (ToF) cameras are subject to high levels of noise and dis...
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07/23/2021
Data-driven deep density estimation
Density estimation plays a crucial role in many data analysis tasks, as ...
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07/13/2020
ProteiNN: Intrinsic-Extrinsic Convolution and Pooling for Scalable Deep Protein Analysis
Proteins perform a large variety of functions in living organisms, thus ...
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03/10/2020
Enabling Viewpoint Learning through Dynamic Label Generation
Optimal viewpoint prediction is an essential task in many computer graph...
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04/16/2019
Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning
We show that denoising of 3D point clouds can be learned unsupervised, d...
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11/12/2018
Deep-learning the Latent Space of Light Transport
We suggest a method to directly deep-learn light transport, i. e., the m...
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06/20/2018
Void Space Surfaces to Convey Depth in Vessel Visualizations
To enhance depth perception and thus data comprehension, additional dept...
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06/05/2018