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04/20/2023
GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models
This paper introduces GenCorres, a novel unsupervised joint shape matchi...
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03/15/2023
DeblurSR: Event-Based Motion Deblurring Under the Spiking Representation
We present DeblurSR, a novel motion deblurring approach that converts a ...
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09/01/2022
Learning Generative Embeddings using an Optimal Subsampling Policy for Tensor Sketching
Data tensors of orders 3 and greater are routinely being generated. Thes...
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03/28/2022
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentation
Hyperspectral images provide a rich representation of the underlying spe...
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03/03/2022
E-CIR: Event-Enhanced Continuous Intensity Recovery
A camera begins to sense light the moment we press the shutter button. D...
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11/15/2021
Recursive Self-Improvement for Camera Image and Signal Processing Pipeline
Current camera image and signal processing pipelines (ISPs), including d...
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10/26/2021
Robust Learning of Physics Informed Neural Networks
Physics-informed Neural Networks (PINNs) have been shown to be effective...
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08/30/2021
Scene Synthesis via Uncertainty-Driven Attribute Synchronization
Developing deep neural networks to generate 3D scenes is a fundamental p...
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08/21/2021
ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators
This paper introduces an unsupervised loss for training parametric defor...
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07/25/2021
Invariance-based Multi-Clustering of Latent Space Embeddings for Equivariant Learning
Variational Autoencoders (VAEs) have been shown to be remarkably effecti...
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04/22/2021
Learning Transferable 3D Adversarial Cloaks for Deep Trained Detectors
This paper presents a novel patch-based adversarial attack pipeline that...
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04/01/2021
Learning Deep Latent Subspaces for Image Denoising
Heterogeneity exists in most camera images. This heterogeneity manifests...
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06/25/2020
Can 3D Adversarial Logos Cloak Humans?
With the trend of adversarial attacks, researchers attempt to fool train...
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10/28/2019
Stein Variational Gradient Descent With Matrix-Valued Kernels
Stein variational gradient descent (SVGD) is a particle-based inference ...
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07/31/2019
SketchyCoreSVD: SketchySVD from Random Subsampling of the Data Matrix
We present a method called SketchyCoreSVD to compute the near-optimal ra...
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02/21/2019
Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization
Fusing a low-resolution hyperspectral image (HSI) and a high-resolution ...
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03/20/2018
Dynamic Sampling Convolutional Neural Networks
We present Dynamic Sampling Convolutional Neural Networks (DSCNN), where...
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10/20/2009
