Hideki Nakayama

research

∙ 08/19/2023

Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific Experts

Bias mitigation in image classification has been widely researched, and ...

0 Jiaxuan Li, et al. ∙

research

∙ 07/18/2023

Revisiting Latent Space of GAN Inversion for Real Image Editing

The exploration of the latent space in StyleGANs and GAN inversion exemp...

0 Kai Katsumata, et al. ∙

research

∙ 07/17/2023

Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data

Label-noise or curated unlabeled data is used to compensate for the assu...

0 Kai Katsumata, et al. ∙

research

∙ 05/31/2023

Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing with StyleGAN Prior Latent Space

The exploration of the latent space in StyleGANs and GAN inversion exemp...

0 Kai Katsumata, et al. ∙

research

∙ 04/17/2023

LED: A Dataset for Life Event Extraction from Dialogs

Lifelogging has gained more attention due to its wide applications, such...

0 Yi-Pei Chen, et al. ∙

research

∙ 04/13/2023

A-CAP: Anticipation Captioning with Commonsense Knowledge

Humans possess the capacity to reason about the future based on a sparse...

0 Duc Minh Vo, et al. ∙

research

∙ 10/16/2022

Character-Centric Story Visualization via Visual Planning and Token Alignment

Story visualization advances the traditional text-to-image generation by...

1 Hong Chen, et al. ∙

research

∙ 10/16/2022

StoryER: Automatic Story Evaluation via Ranking, Rating and Reasoning

Existing automatic story evaluation methods place a premium on story lex...

0 Hong Chen, et al. ∙

research

∙ 09/26/2022

Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video Grounding

This paper explores the task of Temporal Video Grounding (TVG) where, gi...

0 Erica K. Shimomoto, et al. ∙

research

∙ 06/13/2022

Pixel to Binary Embedding Towards Robustness for CNNs

There are several problems with the robustness of Convolutional Neural N...

0 Ikki Kishida, et al. ∙

research

∙ 04/29/2022

OSSGAN: Open-Set Semi-Supervised Image Generation

We introduce a challenging training scheme of conditional GANs, called o...

3 Kai Katsumata, et al. ∙

research

∙ 03/28/2022

NOC-REK: Novel Object Captioning with Retrieved Vocabulary from External Knowledge

Novel object captioning aims at describing objects absent from training ...

0 Duc Minh Vo, et al. ∙

research

∙ 03/16/2022

PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression

We push forward neural network compression research by exploiting a nove...

0 Duc Minh Vo, et al. ∙

research

∙ 10/20/2021

SciXGen: A Scientific Paper Dataset for Context-Aware Text Generation

Generating texts in scientific papers requires not only capturing the co...

0 Hong Chen, et al. ∙

research

∙ 02/09/2021

Graph Energy-based Model for Substructure Preserving Molecular Design

It is common practice for chemists to search chemical databases based on...

0 Ryuichiro Hataya, et al. ∙

research

∙ 02/05/2021

GraphPlan: Story Generation by Planning with Event Graph

Story generation is a task that aims to automatically produce multiple s...

0 Hong Chen, et al. ∙

research

∙ 02/05/2021

Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling

Visual storytelling is a task of generating relevant and interesting sto...

4 Hong Chen, et al. ∙

research

∙ 09/30/2020

Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network

Neural Module Network (NMN) is a machine learning model for solving the ...

0 Yuxuan Wu, et al. ∙

research

∙ 07/24/2020

MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction

Unsupervised learning can discover various unseen diseases, relying on l...

7 Changhee Han, et al. ∙

research

∙ 06/14/2020

Meta Approach to Data Augmentation Optimization

Data augmentation policies drastically improve the performance of image ...

0 Ryuichiro Hataya, et al. ∙

research

∙ 05/02/2020

Single Model Ensemble using Pseudo-Tags and Distinct Vectors

Model ensemble techniques often increase task performance in neural netw...

0 Ryosuke Kuwabara, et al. ∙

research

∙ 01/12/2020

Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems

This work aims to identify/bridge the gap between Artificial Intelligenc...

0 Changhee Han, et al. ∙

research

∙ 11/25/2019

Empirical Study of Easy and Hard Examples in CNN Training

Deep Neural Networks (DNNs) generalize well despite their massive size a...

0 Ikki Kishida, et al. ∙

research

∙ 11/16/2019

Faster AutoAugment: Learning Augmentation Strategies using Backpropagation

Data augmentation methods are indispensable heuristics to boost the perf...

0 Ryuichiro Hataya, et al. ∙

research

∙ 08/20/2019

Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference using a Delta Posterior

Although neural machine translation models reached high translation qual...

0 Raphael Shu, et al. ∙

research

∙ 06/14/2019

GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis

Leveraging large-scale healthy datasets, unsupervised learning can disco...

4 Changhee Han, et al. ∙

research

∙ 06/12/2019

Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detection

Accurate computer-assisted diagnosis, relying on large-scale annotated p...

6 Changhee Han, et al. ∙

research

∙ 05/31/2019

Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection

Convolutional Neural Networks (CNNs) can achieve excellent computer-assi...

0 Changhee Han, et al. ∙

research

∙ 04/17/2019

USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets

Prostate cancer is the most common malignant tumors in men but prostate ...

0 Leonardo Rundo, et al. ∙

research

∙ 03/29/2019

CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study

Prostate cancer is the most common cancer among US men. However, prostat...

0 Leonardo Rundo, et al. ∙

research

∙ 03/29/2019

Infinite Brain MR Images: PGGAN-based Data Augmentation for Tumor Detection

Due to the lack of available annotated medical images, accurate computer...

22 Changhee Han, et al. ∙

research

∙ 03/29/2019

Learning More with Less: GAN-based Medical Image Augmentation

Accurate computer-assisted diagnosis using Convolutional Neural Networks...

0 Changhee Han, et al. ∙

research

∙ 02/26/2019

Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR images

Accurate computer-assisted diagnosis can alleviate the risk of overlooki...

0 Changhee Han, et al. ∙

research

∙ 10/19/2018

Real-time Neural-based Input Method

The input method is an essential service on every mobile and desktop dev...

0 Jiali Yao, et al. ∙

research

∙ 10/16/2018

Semantic Aware Attention Based Deep Object Co-segmentation

Object co-segmentation is the task of segmenting the same objects from m...

0 Hong Chen, et al. ∙

research

∙ 08/14/2018

Discrete Structural Planning for Neural Machine Translation

Structural planning is important for producing long sentences, which is ...

0 Raphael Shu, et al. ∙

research

∙ 01/03/2018

Deep Learning for Forecasting Stock Returns in the Cross-Section

Many studies have been undertaken by using machine learning techniques, ...

0 Masaya Abe, et al. ∙

research

∙ 11/20/2017

Parameter Reference Loss for Unsupervised Domain Adaptation

The success of deep learning in computer vision is mainly attributed to ...

0 Jiren Jin, et al. ∙

research

∙ 11/03/2017

Compressing Word Embeddings via Deep Compositional Code Learning

Natural language processing (NLP) models often require a massive number ...

0 Raphael Shu, et al. ∙

research

∙ 07/06/2017

Single-Queue Decoding for Neural Machine Translation

Neural machine translation models rely on the beam search algorithm for ...

0 Raphael Shu, et al. ∙

research

∙ 04/11/2017

Later-stage Minimum Bayes-Risk Decoding for Neural Machine Translation

For extended periods of time, sequence generation models rely on beam se...

0 Raphael Shu, et al. ∙

research

∙ 12/19/2016

An Empirical Study of Adequate Vision Span for Attention-Based Neural Machine Translation

Recently, the attention mechanism plays a key role to achieve high perfo...

0 Raphael Shu, et al. ∙

research

∙ 11/14/2016

Zero-resource Machine Translation by Multimodal Encoder-decoder Network with Multimedia Pivot

We propose an approach to build a neural machine translation system with...

0 Hideki Nakayama, et al. ∙

research

∙ 04/18/2016

Annotation Order Matters: Recurrent Image Annotator for Arbitrary Length Image Tagging

Automatic image annotation has been an important research topic in facil...

0 Jiren Jin, et al. ∙

Hideki Nakayama

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