Sung Woo Park
Google Scholar / CV / Linkedin
Computer Vision and Machine Learning Lab, Chung-Ang University, Seoul, South Korea.
I am a Ph.D. candidate in the School of Computer Science and Engineering at Chung-Ang University (CAU), advised by Prof. Junseok Kwon. I received M.S. in Computer Science and Engineering and B.S. in Electrical and Electronics Engineering at CAU. I am currently interning with LG AI Research as a research intern.
My research goal is to build probabilistic models upon mathematical disciplines (e.g., optimal transport, Riemannian geometry, differential game, stochastic geometry) and solve challenging real-world tasks. Specifically, my interests include generative modeling, time-series prediction, and uncertainty calibration.
Publications
Sung Woo Park, Hyomin Kim, Hyeseong Kim, and Junseok Kwon, Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS, ICLRW), 2022, Riemannian Neural SDE: Learning Stochastic Representations on Manifolds
Sung Woo Park, and Junseok Kwon, Expert System with Applications (ESWA), 2022, Riemannian Submanifold Framework for Log-Euclidean Metric Learning on Symmetric Positive Definite Manifolds
Sung Woo Park, Kyungjae Lee, and Junseok Kwon, Proc. of International Conference on Learning Representations (ICLR), 2022, Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data
Sung Woo Park, and Junseok Kwon, IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI) 2022, SphereGAN: Sphere Generative Adversarial Network Based on Geometric Moment Matching and Its Applications
Sung Woo Park, and Junseok Kwon, The 38th International Conference on Machine Learning (ICML), 2021, Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Dong Wook Shu, and Junseok Kwon, The 38th International Conference on Machine Learning (ICML), 2021, Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Guisik Kim, Sung Woo Park, and Junseok Kwon, IEEE Transaction on Image Processing (TIP), vol. 30, 2021, Pixel-wise Wasserstein Autoencoder for Highly Generative Dehazing
Sung Woo Park, Dong Wook Shu, and Junseok Kwon, The 34th Annual Conference on Neural Information Processing Systems (NeurIPS), 2020, Deep Diffusion-Invariant Wasserstein Distributional Classification
Dong Wook Shu*, Sung Woo Park*, and Junseok Kwon, International Conference on Computer Vision (ICCV), 2019, 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions (*equal contribution)
Sung Woo Park and Junseok Kwon, Computer Vision and Pattern Recognition (CVPR), Oral presentation, 2019, Sphere Generative Adversarial Network Based on Geometric Moment Matching
Preprints
Sung Woo Park, Byung Woo Park, and Junseok Kwon, Stochastic Differential Game for Network Calibration, Under Review