1 code implementation • 10 Aug 2022 • Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim, Jinwoo Shin, Sung-Ju Lee
Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts between training and testing phases without additional data acquisition or labeling cost; only unlabeled test data streams are used for continual model adaptation.
1 code implementation • 23 Sep 2021 • Seunghyeok Back, Joosoon Lee, Taewon Kim, Sangjun Noh, Raeyoung Kang, Seongho Bak, Kyoobin Lee
Instance-aware segmentation of unseen objects is essential for a robotic system in an unstructured environment.
no code implementations • 27 Feb 2020 • Taewon Kim, Yeseong Park, Youngbin Park, Il Hong Suh
For a robotic grasping task in which diverse unseen target objects exist in a cluttered environment, some deep learning-based methods have achieved state-of-the-art results using visual input directly.