Search Results for author: Joonseok Lee

Found 22 papers, 10 papers with code

MAQA: A Multimodal QA Benchmark for Negation

no code implementations9 Jan 2023 Judith Yue Li, Aren Jansen, Qingqing Huang, Joonseok Lee, Ravi Ganti, Dima Kuzmin

Multimodal learning can benefit from the representation power of pretrained Large Language Models (LLMs).

Question Answering

Towards Efficient Neural Scene Graphs by Learning Consistency Fields

no code implementations9 Oct 2022 Yeji Song, Chaerin Kong, Seoyoung Lee, Nojun Kwak, Joonseok Lee

Neural Radiance Fields (NeRF) achieves photo-realistic image rendering from novel views, and the Neural Scene Graphs (NSG) \cite{ost2021neural} extends it to dynamic scenes (video) with multiple objects.

MuLan: A Joint Embedding of Music Audio and Natural Language

no code implementations26 Aug 2022 Qingqing Huang, Aren Jansen, Joonseok Lee, Ravi Ganti, Judith Yue Li, Daniel P. W. Ellis

Music tagging and content-based retrieval systems have traditionally been constructed using pre-defined ontologies covering a rigid set of music attributes or text queries.

Cross-Modal Retrieval Music Tagging +2

Future Transformer for Long-term Action Anticipation

no code implementations CVPR 2022 Dayoung Gong, Joonseok Lee, Manjin Kim, Seong Jong Ha, Minsu Cho

The task of predicting future actions from a video is crucial for a real-world agent interacting with others.

Action Anticipation

Unconditional Image-Text Pair Generation with Multimodal Cross Quantizer

1 code implementation15 Apr 2022 Hyungyung Lee, Sungjin Park, Joonseok Lee, Edward Choi

To learn a multimodal semantic correlation in a quantized space, we combine VQ-VAE with a Transformer encoder and apply an input masking strategy.

multimodal generation Quantization

Boundary-aware Self-supervised Learning for Video Scene Segmentation

1 code implementation14 Jan 2022 Jonghwan Mun, Minchul Shin, Gunsoo Han, Sangho Lee, Seongsu Ha, Joonseok Lee, Eun-Sol Kim

Inspired from this, we tackle video scene segmentation, which is a task of temporally localizing scene boundaries in a video, with a self-supervised learning framework where we mainly focus on designing effective pretext tasks.

Scene Segmentation Self-Supervised Learning

A Conservative Approach for Unbiased Learning on Unknown Biases

1 code implementation CVPR 2022 Myeongho Jeon, Daekyung Kim, Woochul Lee, Myungjoo Kang, Joonseok Lee

Although convolutional neural networks (CNNs) achieve state-of-the-art in image classification, recent works address their unreliable predictions due to their excessive dependence on biased training data.

Image Classification

Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation

2 code implementations1 Dec 2021 Woncheol Shin, Gyubok Lee, Jiyoung Lee, Joonseok Lee, Edward Choi

Recently, vector-quantized image modeling has demonstrated impressive performance on generation tasks such as text-to-image generation.

Text Generation Text to image generation +2

Boundary-aware Pre-training for Video Scene Segmentation

no code implementations29 Sep 2021 Jonghwan Mun, Minchul Shin, Gunsoo Han, Sangho Lee, Seongsu Ha, Joonseok Lee, Eun-Sol Kim

Inspired from this, we tackle video scene segmentation, which is a task of temporally localizing scene boundaries in a video, with a self-supervised learning framework where we mainly focus on designing effective pretext tasks.

Scene Segmentation Self-Supervised Learning

Session-aware Linear Item-Item Models for Session-based Recommendation

3 code implementations30 Mar 2021 Minjin Choi, jinhong Kim, Joonseok Lee, Hyunjung Shim, Jongwuk Lee

Session-based recommendation aims at predicting the next item given a sequence of previous items consumed in the session, e. g., on e-commerce or multimedia streaming services.

Session-Based Recommendations

Local Collaborative Autoencoders

1 code implementation30 Mar 2021 Minjin Choi, Yoonki Jeong, Joonseok Lee, Jongwuk Lee

Top-N recommendation is a challenging problem because complex and sparse user-item interactions should be adequately addressed to achieve high-quality recommendation results.

A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus

no code implementations18 Nov 2020 BoWen Zhang, Hexiang Hu, Joonseok Lee, Ming Zhao, Sheide Chammas, Vihan Jain, Eugene Ie, Fei Sha

Identifying a short segment in a long video that semantically matches a text query is a challenging task that has important application potentials in language-based video search, browsing, and navigation.

Language Modelling Masked Language Modeling +3

Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation

1 code implementation16 Oct 2020 Sunghyun Park, Kangyeol Kim, Junsoo Lee, Jaegul Choo, Joonseok Lee, Sookyung Kim, Edward Choi

Video generation models often operate under the assumption of fixed frame rates, which leads to suboptimal performance when it comes to handling flexible frame rates (e. g., increasing the frame rate of the more dynamic portion of the video as well as handling missing video frames).

Video Generation

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing

no code implementations3 Jan 2020 Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton

Although essential to revealing biased performance, well intentioned attempts at algorithmic auditing can have effects that may harm the very populations these measures are meant to protect.

Computers and Society

N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification

1 code implementation24 Feb 2018 Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee

Graph Convolutional Networks (GCNs) have shown significant improvements in semi-supervised learning on graph-structured data.

General Classification Node Classification

Network of Graph Convolutional Networks Trained on Random Walks

no code implementations ICLR 2018 Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee

Graph Convolutional Networks (GCNs) are a recently proposed architecture which has had success in semi-supervised learning on graph-structured data.

General Classification Node Classification

Personalized Academic Research Paper Recommendation System

no code implementations19 Apr 2013 Joonseok Lee, Kisung Lee, Jennifer G. Kim

To ease this difficulty, we propose a Personalized Academic Research Paper Recommendation System, which recommends related articles, for each researcher, that may be interesting to her/him.

Collaborative Filtering Recommendation Systems +1

Automatic Feature Induction for Stagewise Collaborative Filtering

no code implementations NeurIPS 2012 Joonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon

Recent approaches to collaborative filtering have concentrated on estimating an algebraic or statistical model, and using the model for predicting missing ratings.

Collaborative Filtering

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