Search Results for author: Jin-Hwa Kim

Found 30 papers, 19 papers with code

Dense Text-to-Image Generation with Attention Modulation

1 code implementation ICCV 2023 Yunji Kim, Jiyoung Lee, Jin-Hwa Kim, Jung-Woo Ha, Jun-Yan Zhu

To address this, we propose DenseDiffusion, a training-free method that adapts a pre-trained text-to-image model to handle such dense captions while offering control over the scene layout.

Query-Efficient Black-Box Red Teaming via Bayesian Optimization

1 code implementation27 May 2023 Deokjae Lee, JunYeong Lee, Jung-Woo Ha, Jin-Hwa Kim, Sang-Woo Lee, Hwaran Lee, Hyun Oh Song

To this end, we propose Bayesian red teaming (BRT), novel query-efficient black-box red teaming methods based on Bayesian optimization, which iteratively identify diverse positive test cases leading to model failures by utilizing the pre-defined user input pool and the past evaluations.

Bayesian Optimization Language Modelling +1

Panoramic Image-to-Image Translation

no code implementations11 Apr 2023 Soohyun Kim, Junho Kim, Taekyung Kim, Hwan Heo, Seungryong Kim, Jiyoung Lee, Jin-Hwa Kim

This task is difficult due to the geometric distortion of panoramic images and the lack of a panoramic image dataset with diverse conditions, like weather or time.

Image-to-Image Translation Translation

Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

1 code implementation14 Mar 2023 Junyoung Seo, Wooseok Jang, Min-Seop Kwak, Jaehoon Ko, Hyeonsu Kim, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, Seungryong Kim

Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural radiance field (NeRF) in the zero-shot setting.

Single-View 3D Reconstruction Text to 3D

UniXGen: A Unified Vision-Language Model for Multi-View Chest X-ray Generation and Report Generation

1 code implementation23 Feb 2023 Hyungyung Lee, Da Young Lee, Wonjae Kim, Jin-Hwa Kim, Tackeun Kim, Jihang Kim, Leonard Sunwoo, Edward Choi

We also find that view-specific special tokens can distinguish between different views and properly generate specific views even if they do not exist in the dataset, and utilizing multi-view chest X-rays can faithfully capture the abnormal findings in the additional X-rays.

Language Modelling Quantization

Robust Camera Pose Refinement for Multi-Resolution Hash Encoding

no code implementations3 Feb 2023 Hwan Heo, Taekyung Kim, Jiyoung Lee, Jaewon Lee, Soohyun Kim, Hyunwoo J. Kim, Jin-Hwa Kim

Multi-resolution hash encoding has recently been proposed to reduce the computational cost of neural renderings, such as NeRF.

Neural Rendering Novel View Synthesis

Semi-Parametric Video-Grounded Text Generation

no code implementations27 Jan 2023 Sungdong Kim, Jin-Hwa Kim, Jiyoung Lee, Minjoon Seo

Efficient video-language modeling should consider the computational cost because of a large, sometimes intractable, number of video frames.

Language Modelling Text Generation +2

SelecMix: Debiased Learning by Contradicting-pair Sampling

1 code implementation4 Nov 2022 Inwoo Hwang, Sangjun Lee, Yunhyeok Kwak, Seong Joon Oh, Damien Teney, Jin-Hwa Kim, Byoung-Tak Zhang

Experiments on standard benchmarks demonstrate the effectiveness of the method, in particular when label noise complicates the identification of bias-conflicting examples.

Modal-specific Pseudo Query Generation for Video Corpus Moment Retrieval

1 code implementation23 Oct 2022 Minjoon Jung, SeongHo Choi, Joochan Kim, Jin-Hwa Kim, Byoung-Tak Zhang

Video corpus moment retrieval (VCMR) is the task to retrieve the most relevant video moment from a large video corpus using a natural language query.

Moment Retrieval Retrieval +2

AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models

no code implementations8 Oct 2022 Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee

To combine parameter-efficient adaptation and model compression, we propose AlphaTuning consisting of post-training quantization of the pre-trained language model and fine-tuning only some parts of quantized parameters for a target task.

Language Modelling Model Compression +1

Mutual Information Divergence: A Unified Metric for Multimodal Generative Models

1 code implementation25 May 2022 Jin-Hwa Kim, Yunji Kim, Jiyoung Lee, Kang Min Yoo, Sang-Woo Lee

Based on a recent trend that multimodal generative evaluations exploit a vison-and-language pre-trained model, we propose the negative Gaussian cross-mutual information using the CLIP features as a unified metric, coined by Mutual Information Divergence (MID).

Hallucination Pair-wise Detection (1-ref) Hallucination Pair-wise Detection (4-ref) +4

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning

no code implementations11 May 2022 Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song, Se-Young Yun

Cross-domain few-shot learning (CD-FSL), where there are few target samples under extreme differences between source and target domains, has recently attracted huge attention.

cross-domain few-shot learning Transfer Learning

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

2 code implementations1 Feb 2022 Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song, Se-Young Yun

This data enables self-supervised pre-training on the target domain, in addition to supervised pre-training on the source domain.

cross-domain few-shot learning

Logit As Auxiliary Weak-supervision for More Reliable and Accurate Prediction

no code implementations1 Jan 2021 Duhyeon Bang, Yunho Jeon, Jin-Hwa Kim, Jiwon Kim, Hyunjung Shim

When a person identifies objects, he or she can think by associating objects to many classes and conclude by taking inter-class relations into account.

Data Augmentation

Multi-step Estimation for Gradient-based Meta-learning

no code implementations8 Jun 2020 Jin-Hwa Kim, Junyoung Park, Yongseok Choi

To validate our method, we experiment on meta-transfer learning and few-shot learning tasks for multiple settings.

Few-Shot Learning Transfer Learning

Bilinear Attention Networks

8 code implementations NeurIPS 2018 Jin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang

In this paper, we propose bilinear attention networks (BAN) that find bilinear attention distributions to utilize given vision-language information seamlessly.

Visual Question Answering

Visual Explanations from Hadamard Product in Multimodal Deep Networks

no code implementations18 Dec 2017 Jin-Hwa Kim, Byoung-Tak Zhang

Kim et al. (2016) show that the Hadamard product in multimodal deep networks, which is well-known for the joint function of visual question answering tasks, implicitly performs an attentional mechanism for visual inputs.

Question Answering Visual Question Answering

Overcoming Catastrophic Forgetting by Incremental Moment Matching

1 code implementation NeurIPS 2017 Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, Jung-Woo Ha, Byoung-Tak Zhang

Catastrophic forgetting is a problem of neural networks that loses the information of the first task after training the second task.

Transfer Learning

rnn : Recurrent Library for Torch

1 code implementation24 Nov 2015 Nicholas Léonard, Sagar Waghmare, Yang Wang, Jin-Hwa Kim

The rnn package provides components for implementing a wide range of Recurrent Neural Networks.

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