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07/04/2023
AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation
Few-shot image generation (FSIG) aims to learn to generate new and diver...
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05/26/2023
On Evaluating Adversarial Robustness of Large Vision-Language Models
Large vision-language models (VLMs) such as GPT-4 have achieved unpreced...
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03/17/2023
A Recipe for Watermarking Diffusion Models
Recently, diffusion models (DMs) have demonstrated their advantageous po...
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08/24/2022
Discovering Transferable Forensic Features for CNN-generated Images Detection
Visual counterfeits are increasingly causing an existential conundrum in...
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08/23/2022
FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification
Conventional Few-shot classification (FSC) aims to recognize samples fro...
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07/31/2022
Neural Correlates of Face Familiarity Perception
In the domain of face recognition, there exists a puzzling timing discre...
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06/29/2022
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?
This work investigates the compatibility between label smoothing (LS) an...
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05/08/2022
A Closer Look at Few-shot Image Generation
Modern GANs excel at generating high quality and diverse images. However...
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12/16/2021
Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning
Unsupervised graph-level representation learning plays a crucial role in...
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10/24/2021
Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples
Few-shot classifiers have been shown to exhibit promising results in use...
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07/16/2021
Measuring Fairness in Generative Models
Deep generative models have made much progress in improving training sta...
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03/31/2021
A Closer Look at Fourier Spectrum Discrepancies for CNN-generated Images Detection
CNN-based generative modelling has evolved to produce synthetic images i...
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07/17/2020
Explanation-Guided Training for Cross-Domain Few-Shot Classification
Cross-domain few-shot classification task (CD-FSC) combines few-shot cla...
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06/09/2020
Towards Good Practices for Data Augmentation in GAN Training
Recent successes in Generative Adversarial Networks (GAN) have affirmed ...
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11/16/2019
Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game
Self-supervised (SS) learning is a powerful approach for representation ...
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09/14/2019
Optimized Routing and Spectrum Assignment for Video Communication over an Elastic Optical Network
Elastic optical network (EON) efficiently utilize spectral resources for...
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07/06/2019
TEAGS: Time-aware Text Embedding Approach to Generate Subgraphs
Contagions (e.g. virus, gossip) spread over the nodes in propagation gra...
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07/06/2019
TEALS: Time-aware Text Embedding Approach to Leverage Subgraphs
Given a graph over which the contagions (e.g. virus, gossip) propagate, ...
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05/14/2019
An Improved Self-supervised GAN via Adversarial Training
We propose to improve unconditional Generative Adversarial Networks (GAN...
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04/24/2019
Simultaneous Feature Aggregating and Hashing for Compact Binary Code Learning
Representing images by compact hash codes is an attractive approach for ...
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04/06/2019
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences
This paper presents a novel randomized algorithm for robust point cloud ...
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03/01/2019
Detecting Target-Area Link-Flooding DDoS Attacks using Traffic Analysis and Supervised Learning
A novel class of extreme link-flooding DDoS (Distributed Denial of Servi...
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11/04/2018
Improving GAN with neighbors embedding and gradient matching
We propose two new techniques for training Generative Adversarial Networ...
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08/23/2018
DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN
Recently, the introduction of the generative adversarial network (GAN) a...
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08/22/2018
Deep Adaptive Temporal Pooling for Activity Recognition
Deep neural networks have recently achieved competitive accuracy for hum...
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08/06/2018
Defense Against Adversarial Attacks with Saak Transform
Deep neural networks (DNNs) are known to be vulnerable to adversarial pe...
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06/17/2018
MCP: a Multi-Component learning machine to Predict protein secondary structure
The Gene or DNA sequence in every cell does not control genetic properti...
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06/17/2018
MCP: a multi-component learning machine for prediction of protein secondary structure
Proteins biological function is tightly connected to its specific 3D str...
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03/30/2018
Efficient and Deep Person Re-Identification using Multi-Level Similarity
Person Re-Identification (ReID) requires comparing two images of person ...
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03/23/2018
Generative Adversarial Autoencoder Networks
We introduce an effective model to overcome the problem of mode collapse...
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02/28/2018
Fine-grained wound tissue analysis using deep neural network
Tissue assessment for chronic wounds is the basis of wound grading and s...
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02/21/2018
Binary Constrained Deep Hashing Network for Image Retrieval without Human Intervention
Learning compact binary codes for image retrieval problem using deep neu...
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02/19/2018
Simultaneous Compression and Quantization: A Joint Approach for Efficient Unsupervised Hashing
The two most important requirements for unsupervised data-dependent hash...
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02/10/2018
On-device Scalable Image-based Localization
We present the scalable design of an entire on-device system for large-s...
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02/07/2018
From Selective Deep Convolutional Features to Compact Binary Representations for Image Retrieval
Convolutional Neural Network (CNN) is a very powerful approach to extrac...
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12/31/2017
Early detection of Crossfire attacks using deep learning
Crossfire attack is a recently proposed threat designed to disconnect wh...
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12/26/2017
Aircraft Fuselage Defect Detection using Deep Neural Networks
To ensure flight safety of aircraft structures, it is necessary to have ...
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12/08/2017
Compact Hash Code Learning with Binary Deep Neural Network
In this work, we firstly propose deep network models and learning algori...
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12/04/2017
Adaptive Quantization for Deep Neural Network
In recent years Deep Neural Networks (DNNs) have been rapidly developed ...
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11/24/2017
Supervised Hashing with End-to-End Binary Deep Neural Network
Image hashing is a popular technique applied to large scale content-base...
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07/04/2017
Selective Deep Convolutional Features for Image Retrieval
Convolutional Neural Network (CNN) is a very powerful approach to extrac...
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06/17/2017
Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text
The YouTube-8M video classification challenge requires teams to classify...
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05/13/2017
Deep neural networks on graph signals for brain imaging analysis
Brain imaging data such as EEG or MEG are high-dimensional spatiotempora...
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04/06/2017
Enhance Feature Discrimination for Unsupervised Hashing
We introduce a novel approach to improve unsupervised hashing. Specifica...
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04/04/2017
Simultaneous Feature Aggregating and Hashing for Large-scale Image Search
In most state-of-the-art hashing-based visual search systems, local imag...
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01/08/2017
On Classification of Distorted Images with Deep Convolutional Neural Networks
Image blur and image noise are common distortions during image acquisiti...
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09/26/2016
Simultaneous Low-rank Component and Graph Estimation for High-dimensional Graph Signals: Application to Brain Imaging
We propose an algorithm to uncover the intrinsic low-rank component of a...
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05/23/2016
Embedding based on function approximation for large scale image search
The objective of this paper is to design an embedding method that maps l...
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01/25/2016
Egocentric Activity Recognition with Multimodal Fisher Vector
With the increasing availability of wearable devices, research on egocen...
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01/06/2016
