no code implementations • 13 Sep 2023 • Namhyuk Ahn, Junsoo Lee, Chunggi Lee, Kunhee Kim, Daesik Kim, Seung-Hun Nam, Kibeom Hong
Recent progresses in large-scale text-to-image models have yielded remarkable accomplishments, finding various applications in art domain.
1 code implementation • 26 Oct 2022 • Hyunwook Lee, Chunggi Lee, Hongkyu Lim, Sungahn Ko
In this paper, we examine the definition of shape and distortions, which are crucial for shape-awareness in time-series forecasting, and provide a design rationale for the shape-aware loss function.
no code implementations • 11 Oct 2022 • Cholmin Kang, Chunggi Lee, Heon Song, Minuk Ma, S ergio Pereira
Furthermore, models trained from data annotated with lower inter-labeler variability outperform those from higher inter-labeler variability.
1 code implementation • CVPR 2022 • Chunggi Lee, Seonwook Park, Heon Song, Jeongun Ryu, Sanghoon Kim, Haejoon Kim, Sérgio Pereira, Donggeun Yoo
We perform experiments on the Tiny-DOTA and LCell datasets using both two-stage and one-stage object detection architectures to verify the efficacy of our approach.
1 code implementation • 29 Nov 2019 • Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Kihwan Kim, Seungmin Jin, Sungahn Ko, Jaegul Choo
Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamically changing spatial dependencies among roads and temporal patterns over long input sequences.