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07/04/2023
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
Memorization of training data is an active research area, yet our unders...
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06/01/2023
The Hidden Language of Diffusion Models
Text-to-image diffusion models have demonstrated an unparalleled ability...
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05/05/2023
Reconstructing Training Data from Multiclass Neural Networks
Reconstructing samples from the training set of trained neural networks ...
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02/23/2023
Teaching CLIP to Count to Ten
Large vision-language models (VLMs), such as CLIP, learn rich joint imag...
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11/21/2022
SinFusion: Training Diffusion Models on a Single Image or Video
Diffusion models exhibited tremendous progress in image and video genera...
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10/17/2022
Imagic: Text-Based Real Image Editing with Diffusion Models
Text-conditioned image editing has recently attracted considerable inter...
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07/24/2022
Combining Internal and External Constraints for Unrolling Shutter in Videos
Videos obtained by rolling-shutter (RS) cameras result in spatially-dist...
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06/15/2022
Reconstructing Training Data from Trained Neural Networks
Understanding to what extent neural networks memorize training data is a...
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06/07/2022
A Penny for Your (visual) Thoughts: Self-Supervised Reconstruction of Natural Movies from Brain Activity
Reconstructing natural videos from fMRI brain recordings is very challen...
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05/11/2022
Diverse Video Generation from a Single Video
GANs are able to perform generation and manipulation tasks, trained on a...
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12/16/2021
Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images
Despite remarkable progress on visual recognition tasks, deep neural-net...
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09/17/2021
Diverse Generation from a Single Video Made Possible
Most advanced video generation and manipulation methods train on a large...
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06/09/2021
More than meets the eye: Self-supervised depth reconstruction from brain activity
In the past few years, significant advancements were made in reconstruct...
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04/27/2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Image classification models can depend on multiple different semantic at...
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03/29/2021
Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
Single image generative models perform synthesis and manipulation tasks ...
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06/19/2020
From Discrete to Continuous Convolution Layers
A basic operation in Convolutional Neural Networks (CNNs) is spatial res...
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04/13/2020
SpeedNet: Learning the Speediness in Videos
We wish to automatically predict the "speediness" of moving objects in v...
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03/19/2020
Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning
When a very fast dynamic event is recorded with a low-framerate camera, ...
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03/13/2020
Semantic Pyramid for Image Generation
We present a novel GAN-based model that utilizes the space of deep featu...
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09/14/2019
Blind Super-Resolution Kernel Estimation using an Internal-GAN
Super resolution (SR) methods typically assume that the low-resolution (...
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07/03/2019
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Reconstructing observed images from fMRI brain recordings is challenging...
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02/01/2019
Natural and Adversarial Error Detection using Invariance to Image Transformations
We propose an approach to distinguish between correct and incorrect imag...
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12/02/2018
"Double-DIP": Unsupervised Image Decomposition via Coupled Deep-Image-Priors
Many seemingly unrelated computer vision tasks can be viewed as a specia...
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12/01/2018
Internal Distribution Matching for Natural Image Retargeting
Good Visual Retargeting changes the global size and aspect ratio of a na...
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12/17/2017
"Zero-Shot" Super-Resolution using Deep Internal Learning
Deep Learning has led to a dramatic leap in Super-Resolution (SR) perfor...
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12/14/2016