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04/29/2022
Flamingo: a Visual Language Model for Few-Shot Learning
Building models that can be rapidly adapted to numerous tasks using only...
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10/28/2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
The instability of Generative Adversarial Network (GAN) training has fre...
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06/05/2020
End-to-End Adversarial Text-to-Speech
Modern text-to-speech synthesis pipelines typically involve multiple pro...
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12/02/2019
LOGAN: Latent Optimisation for Generative Adversarial Networks
Training generative adversarial networks requires balancing of delicate ...
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09/25/2019
High Fidelity Speech Synthesis with Adversarial Networks
Generative adversarial networks have seen rapid development in recent ye...
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07/15/2019
Efficient Video Generation on Complex Datasets
Generative models of natural images have progressed towards high fidelit...
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07/04/2019
Large Scale Adversarial Representation Learning
Adversarially trained generative models (GANs) have recently achieved co...
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09/28/2018
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Despite recent progress in generative image modeling, successfully gener...
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11/27/2017
Population Based Training of Neural Networks
Neural networks dominate the modern machine learning landscape, but thei...
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05/31/2016
Adversarial Feature Learning
The ability of the Generative Adversarial Networks (GANs) framework to l...
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04/25/2016
Context Encoders: Feature Learning by Inpainting
We present an unsupervised visual feature learning algorithm driven by c...
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03/28/2016
Generating Visual Explanations
Clearly explaining a rationale for a classification decision to an end-u...
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05/28/2015
Visual Search at Pinterest
We demonstrate that, with the availability of distributed computation pl...
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05/03/2015
Sequence to Sequence -- Video to Text
Real-world videos often have complex dynamics; and methods for generatin...
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12/15/2014
Translating Videos to Natural Language Using Deep Recurrent Neural Networks
Solving the visual symbol grounding problem has long been a goal of arti...
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11/17/2014
Long-term Recurrent Convolutional Networks for Visual Recognition and Description
Models based on deep convolutional networks have dominated recent image ...
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07/18/2014
LSDA: Large Scale Detection Through Adaptation
A major challenge in scaling object detection is the difficulty of obtai...
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07/15/2014
Part-based R-CNNs for Fine-grained Category Detection
Semantic part localization can facilitate fine-grained categorization by...
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06/20/2014
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe provides multimedia scientists and practitioners with a clean and ...
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12/21/2013
One-Shot Adaptation of Supervised Deep Convolutional Models
Dataset bias remains a significant barrier towards solving real world co...
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11/11/2013
Rich feature hierarchies for accurate object detection and semantic segmentation
Object detection performance, as measured on the canonical PASCAL VOC da...
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10/06/2013
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
We evaluate whether features extracted from the activation of a deep con...
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08/20/2013