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08/11/2023
DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity
The unprecedented photorealistic results achieved by recent text-to-imag...
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05/15/2023
Improved baselines for vision-language pre-training
Contrastive learning has emerged as an efficient framework to learn mult...
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04/26/2023
Controllable Image Generation via Collage Representations
Recent advances in conditional generative image models have enabled impr...
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03/16/2023
Instance-Conditioned GAN Data Augmentation for Representation Learning
Data augmentation has become a crucial component to train state-of-the-a...
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02/15/2023
Learning to Substitute Ingredients in Recipes
Recipe personalization through ingredient substitution has the potential...
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11/03/2022
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
Deep learning vision systems are widely deployed across applications whe...
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10/03/2022
Uncertainty-Driven Active Vision for Implicit Scene Reconstruction
Multi-view implicit scene reconstruction methods have become increasingl...
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03/30/2022
On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction
Most current approaches to undersampled multi-coil MRI reconstruction fo...
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10/25/2021
Parameter Prediction for Unseen Deep Architectures
Deep learning has been successful in automating the design of features i...
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09/10/2021
Instance-Conditioned GAN
Generative Adversarial Networks (GANs) can generate near photo realistic...
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07/20/2021
Active 3D Shape Reconstruction from Vision and Touch
Humans build 3D understandings of the world through active object explor...
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12/07/2020
Generating unseen complex scenes: are we there yet?
Although recent complex scene conditional generation models generate inc...
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07/30/2020
Instance Selection for GANs
Recent advances in Generative Adversarial Networks (GANs) have led to th...
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07/20/2020
Active MR k-space Sampling with Reinforcement Learning
Deep learning approaches have recently shown great promise in accelerati...
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07/07/2020
3D Shape Reconstruction from Vision and Touch
When a toddler is presented a new toy, their instinctual behaviour is to...
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04/15/2020
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning
We focus on the problem of training convolutional neural networks on gig...
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08/16/2019
Needles in Haystacks: On Classifying Tiny Objects in Large Images
In some computer vision domains, such as medical or hyperspectral imagin...
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07/11/2019
On the Evaluation of Conditional GANs
Conditional Generative Adversarial Networks (cGANs) are finding increasi...
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04/11/2019
Elucidating image-to-set prediction: An analysis of models, losses and datasets
In recent years, we have experienced a flurry of contributions in the mu...
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02/08/2019
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition
The goal of MRI reconstruction is to restore a high fidelity image from ...
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01/13/2019
The Liver Tumor Segmentation Benchmark (LiTS)
In this work, we report the set-up and results of the Liver Tumor Segmen...
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12/14/2018
Inverse Cooking: Recipe Generation from Food Images
People enjoy food photography because they appreciate food. Behind each ...
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11/21/2018
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measuremen...
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04/30/2018
On the iterative refinement of densely connected representation levels for semantic segmentation
State-of-the-art semantic segmentation approaches increase the receptive...
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10/06/2017
Learnable Explicit Density for Continuous Latent Space and Variational Inference
In this paper, we study two aspects of the variational autoencoder (VAE)...
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05/21/2017
Image Segmentation by Iterative Inference from Conditional Score Estimation
Inspired by the combination of feedforward and iterative computations in...
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12/02/2016
A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images
Colorectal cancer (CRC) is the third cause of cancer death worldwide. Cu...
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11/28/2016
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
State-of-the-art approaches for semantic image segmentation are built on...
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08/14/2016
The Importance of Skip Connections in Biomedical Image Segmentation
In this paper, we study the influence of both long and short skip connec...
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07/26/2016
