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Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis
Training Generative Adversarial Networks (GAN) on high-fidelity images u...
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Self-Supervised Sketch-to-Image Synthesis
Imagining a colored realistic image from an arbitrarily drawn sketch is ...
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Spatial Frequency Bias in Convolutional Generative Adversarial Networks
As the success of Generative Adversarial Networks (GANs) on natural imag...
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TIME: Text and Image Mutual-Translation Adversarial Networks
Focusing on text-to-image (T2I) generation, we propose Text and Image Mu...
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Sketch-to-Art: Synthesizing Stylized Art Images From Sketches
We propose a new approach for synthesizing fully detailed art-stylized i...
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2nd Place Solution to the GQA Challenge 2019
We present a simple method that achieves unexpectedly superior performan...
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OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization
Exploring the potential of GANs for unsupervised disentanglement learnin...
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Learning Feature-to-Feature Translator by Alternating Back-Propagation for Zero-Shot Learning
We investigate learning feature-to-feature translator networks by altern...
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Graphical Contrastive Losses for Scene Graph Generation
Most scene graph generators use a two-stage pipeline to detect visual re...
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Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning
Zero-shot learning extends the conventional object classification to the...
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An Interpretable Model for Scene Graph Generation
We propose an efficient and interpretable scene graph generator. We cons...
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Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge
This article describes the model we built that achieved 1st place in the...
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Disconnected Manifold Learning for Generative Adversarial Networks
Real images often lie on a union of disjoint manifolds rather than one g...
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Large-Scale Visual Relationship Understanding
Large scale visual understanding is challenging, as it requires a model ...
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The Shape of Art History in the Eyes of the Machine
How does the machine classify styles in art? And how does it relate to a...
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Imagine it for me: Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts
Most existing zero-shot learning methods consider the problem as a visua...
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Picasso, Matisse, or a Fake? Automated Analysis of Drawings at the Stroke Level for Attribution and Authentication
This paper proposes a computational approach for analysis of strokes in ...
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Link the head to the "beak": Zero Shot Learning from Noisy Text Description at Part Precision
In this paper, we study learning visual classifiers from unstructured te...
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A Multilayer-Based Framework for Online Background Subtraction with Freely Moving Cameras
The exponentially increasing use of moving platforms for video capture i...
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CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms
We propose a new system for generating art. The system generates art by ...
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Overlapping Cover Local Regression Machines
We present the Overlapping Domain Cover (ODC) notion for kernel machines...
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Modelling depth for nonparametric foreground segmentation using RGBD devices
The problem of detecting changes in a scene and segmenting the foregroun...
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Automatic Annotation of Structured Facts in Images
Motivated by the application of fact-level image understanding, we prese...
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The Role of Typicality in Object Classification: Improving The Generalization Capacity of Convolutional Neural Networks
Deep artificial neural networks have made remarkable progress in differe...
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Manifold-Kernels Comparison in MKPLS for Visual Speech Recognition
Speech recognition is a challenging problem. Due to the acoustic limitat...
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Learning Kernels for Structured Prediction using Polynomial Kernel Transformations
Learning the kernel functions used in kernel methods has been a vastly e...
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Supervised Dimensionality Reduction via Distance Correlation Maximization
In our work, we propose a novel formulation for supervised dimensionalit...
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Write a Classifier: Predicting Visual Classifiers from Unstructured Text
People typically learn through exposure to visual concepts associated wi...
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Toward a Taxonomy and Computational Models of Abnormalities in Images
The human visual system can spot an abnormal image, and reason about wha...
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Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos
We propose a new zero-shot Event Detection method by Multi-modal Distrib...
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Convolutional Models for Joint Object Categorization and Pose Estimation
In the task of Object Recognition, there exists a dichotomy between the ...
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Sherlock: Scalable Fact Learning in Images
We study scalable and uniform understanding of facts in images. Existing...
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Tell and Predict: Kernel Classifier Prediction for Unseen Visual Classes from Unstructured Text Descriptions
In this paper we propose a framework for predicting kernelized classifie...
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Quantifying Creativity in Art Networks
Can we develop a computer algorithm that assesses the creativity of a pa...
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Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature
In the past few years, the number of fine-art collections that are digit...
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Factorization of View-Object Manifolds for Joint Object Recognition and Pose Estimation
Due to large variations in shape, appearance, and viewing conditions, ob...
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Learning Hypergraph-regularized Attribute Predictors
We present a novel attribute learning framework named Hypergraph-based A...
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Abnormal Object Recognition: A Comprehensive Study
When describing images, humans tend not to talk about the obvious, but r...
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On The Effect of Hyperedge Weights On Hypergraph Learning
Hypergraph is a powerful representation in several computer vision, mach...
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Computational Beauty: Aesthetic Judgment at the Intersection of Art and Science
In part one of the Critique of Judgment, Immanuel Kant wrote that "the j...
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Generalized Twin Gaussian Processes using Sharma-Mittal Divergence
There has been a growing interest in mutual information measures due to ...
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Toward Automated Discovery of Artistic Influence
Considering the huge amount of art pieces that exist, there is valuable ...
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Collaborative Discriminant Locality Preserving Projections With its Application to Face Recognition
We present a novel Discriminant Locality Preserving Projections (DLPP) a...
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Visual-Semantic Scene Understanding by Sharing Labels in a Context Network
We consider the problem of naming objects in complex, natural scenes con...
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DISCOMAX: A Proximity-Preserving Distance Correlation Maximization Algorithm
In a regression setting we propose algorithms that reduce the dimensiona...
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Learning Hypergraph Labeling for Feature Matching
This study poses the feature correspondence problem as a hypergraph node...
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