Generation Research
Generation Research at NAVER AI Lab
We contribute to the global development of AI technology by pushing the boundaries of visual generation and supporting users' creative activities by providing high-quality generations. Furthermore, it enables new business models by leveraging the power of AI generation to create virtual characters, objects, and environments. We welcome strong candidates with diverse research experiences and leadership skills, having publications presented at top-tier venues. Join us on the journey of innovation and excellence!
Our research interests include:
Multimodal generation models
Neural 3D representation learning and its applications
Generative applications tailored for LLMs
Hiring Research Scientists
We are seeking globally competitive research scientists to join our team and work on advancing generation research. As an individual research scientist, you will have the opportunity to lead your own research projects and collaborate on international projects with our associate research centers.
What you will do:
Research and develop novel methods related to 2D/3D generations
Publish original papers to top-tier academic venues
Collaborate with our colleague researchers and mentor interns
Communicate and collaborate with prominent external researchers
Requirements
Holds a PhD degree or equivalent (or expected to receive within 6 months) in Computer Science (CS), Electrical Engineering (EE), or other relevant fields
Academic publication records at top-tier conferences and journals in Machine Learning and Computer Vision
Comprehensive experience in research collaborations and academic writing in related fields
Excellent communication skills
How to Apply
Please submit your application via this platform to register for our Talent Pool (available in Korean/ English), where sign-in is required.
Application category: Tech > Common > Common > AI (Full-time)
Please be advised that the hiring process could extend up to three months. If you have a deadline for another offer, we encourage you to reach out to HR for further assistance.
Hiring Research Interns
We are hiring around three research interns per half-year. As an intern, you will participate in a research project aimed at one of the top-tier publication venues. You may also participate in other projects and engage in discussions to broaden your research experience.
What you will be doing:
Explore and conduct research to publish a solid work
Study and share relevant works
Communicate and collaborate with team members
Requirements
Pursuing a M.S/PhD or equivalent in Computer Science (CS), Electrical Engineering (EE), or other relevant fields
Experience as a lead author for a top-tier venue
How to Apply
Selected Publications
NAVER AI Lab employees are distinguished by being displayed in bold text. The corresponding authors and equal contributions are denoted by asterisks (*) and carets (^), respectively. When a single author takes the lead and the last author signifies the corresponding author, we omit the notation briefly.
2024
Polyhedral Complex Derivation from Piecewise Trilinear Networks. Jin-Hwa Kim (NAVER AI Lab, SNU AIIS), arXiv 2024. [arXiv]
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation. Junyoung Seo^ (Korea Univ.), Wooseok Jang^ (Korea University), Min-Seop Kwak^ (Korea Univ.), Hyeonsu Kim (Korea University), Jaehoon Ko (Korea University), Junho Kim (NAVER AI Lab), Jin-Hwa Kim* (NAVER AI Lab, SNU AIIS), Jiyoung Lee* (NAVER AI Lab), Seungryong Kim* (Korea Univ.). ICLR 2024. [Paper][Project][Code][Threestudio]
2023
3D-aware Blending with Generative NeRFs. Hyunsu Kim (NAVER AI Lab), Gayoung Lee (NAVER AI Lab), Yunjey Choi (NAVER AI Lab), Jin-Hwa Kim (NAVER AI Lab, SNU AIIS), Jun-Yan Zhu (CMU). ICCV 2023.
Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models. Jaewoong Lee (KAIST), Sangwon Jang (Yonsei Univ.), Jaehyeong Jo (KAIST), Jaehong Yoon (KAIST), Yunji Kim (NAVER AI Lab), Jin-Hwa Kim (NAVER AI Lab, SNU AIIS), Jung-Woo Ha (NAVER AI Lab), Sung Ju Hwang (KAIST), ICCV 2023.
Dense Text-to-Image Generation with Attention Modulation. Yunji Kim (NAVER AI Lab), Jiyoung Lee (NAVER AI Lab), Jin-Hwa Kim (NAVER AI Lab, SNU AIIS), Jung-Woo Ha (NAVER AI Lab), Jun-Yan Zhu (CMU). ICCV 2023.
Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding. Gyeongman Kim (KAIST), Hajin Shim (KAIST), Hyunsu Kim (NAVER AI Lab), Yunjey Choi (NAVER AI Lab), Junho Kim (NAVER AI Lab), Eunho Yang (KAIST). CVPR 2023.
Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models. Jooyoung Choi (SNU), Yunjey Choi (NAVER AI Lab), Yunji Kim (NAVER AI Lab), Junho Kim (NAVER AI Lab). CVPR AI4CC Workshop Oral 2023.
UniXGen: A Unified Vision-Language Model for Multi-View Chest X-ray Generation and Report Generation. Hyungyung Lee (KAIST), Da Young Lee (Deep-in-Sight Co.), Wonjae Kim (NAVER AI Lab), Jin-Hwa Kim (NAVER AI Lab, SNU AIIS), Tackeun Kim (Seoul National Bundang Hospital), Jihang Kim (Seoul National Bundang Hospital), Leonard Sunwoo (Seoul National Bundang Hospital), Edward Choi (KAIST). ArXiv 2023.
Panoramic Image-to-Image Translation. Soohyun Kim (Korea Univ.), Junho Kim (NAVER AI Lab), Taekyung Kim (NAVER AI Lab), Hwan Heo (Korea Univ.), Seungryong Kim* (Korea Univ.), Jiyoung Lee* (NAVER AI Lab), Jin-Hwa Kim* (NAVER AI Lab, SNU AIIS). ArXiv 2023.
Robust Camera Pose Refinement for Multi-Resolution Hash Encoding. Hwan Heo (Korea Univ.), Taekyung Kim (NAVER AI Lab), Jiyoung Lee (NAVER AI Lab), Jaewon Lee (Korea Univ.), Soohyun Kim (Korea Univ.), Hyunwoo J. Kim* (Korea Univ.), Jin-Hwa Kim* (NAVER AI Lab, SNU AIIS). ICML 2023.
Rarity Score: A New Metric to Evaluate the Uncommonness of Synthesized Images. Jiyeon Han (KAIST), Hwanil Choi (KAIST), Yunjey Choi (NAVER AI Lab), Junho Kim (NAVER AI Lab), Jung-Woo Ha (NAVER AI Lab), Jaesik Choi (KAIST). ICLR 2023 Spotlight.
Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance. Yoonjeon Kim (KAIST), Hyunsu Kim (NAVER AI Lab), Junho Kim (NAVER AI Lab), Yunjey Choi (NAVER AI Lab), Eunho Yang (KAIST). ICLR 2023.
2022
Mutual Information Divergence: A Unified Metric for Multimodal Generative Models. Jin-Hwa Kim* (NAVER AI Lab, SNU AIIS), Yunji Kim (NAVER AI Lab), Jiyoung Lee (NAVER AI Lab), Kang Min Yoo (NAVER AI Lab), Sang-Woo Lee (NAVER CLOVA). NeurIPS 2022.
Generator Knows What Discriminator Should Learn in Unconditional GANs. Gayoung Lee (NAVER AI Lab), Hyunsu Kim (NAVER AI Lab), Junho Kim (NAVER AI Lab), Seonghyeon Kim (NAVER CLOVA), Jung-Woo Ha (NAVER AI Lab), Yunjey Choi (NAVER AI Lab). ECCV 2022.
Feature Statistics Mixing Regularization for Generative Adversarial Networks. Junho Kim (NAVER AI Lab), Yunjey Choi (NAVER AI Lab), Youngjung Uh (Yonsei Univ.). CVPR 2022.
Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks. Sihyun Yu (KAIST), Jihoon Tack (KAIST), Sangwoo Mo (KAIST), Hyunsu Kim (NAVER AI Lab), Junho Kim (NAVER AI Lab), Jung-Woo Ha (NAVER AI Lab), Jinwoo Shin (KAIST). ICLR 2022.
2021
Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing. Hyunsu Kim (NAVER AI Lab), Yunjey Choi (NAVER AI Lab), Junho Kim (NAVER AI Lab), Sungjoo Yoo (SNU), Youngjung Uh (Yonsei Univ.). CVPR 2021.
Rethinking the Truly Unsupervised Image-to-Image Translation. Kyungjune Baek (Yonsei Univ.), Yunjey Choi (NAVER AI Lab), Youngjung Uh (Yonsei Univ.), Jaejun Yoo (EPFL), Hyunjung Shim (Yonsei U.). ICCV 2021.
Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing. Hyunsu Kim (NAVER AI Lab), Yunjey Choi (NAVER AI Lab), Junho Kim (NAVER AI Lab), Sungjoo Yoo (SNU), Youngjung Uh (Yonsei Univ.). CVPR 2021.
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