activity
20202023
most citedSparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

92 citations · 98 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2023

ELVIS: Empowering Locality of Vision Language Pre-training with Intra-modal Similarity

Sumin Seo, JaeWoong Shin, Jaewoo Kang +2

Deep learning has shown great potential in assisting radiologists in reading chest X-ray (CXR) images, but its need for expensive annotations for improving performance prevents wid…

eess.IV2023★ 2 cited

OCELOT: Overlapped Cell on Tissue Dataset for Histopathology

Jeongun Ryu, Aaron Valero Puche, JaeWoong Shin +9

Cell detection is a fundamental task in computational pathology that can be used for extracting high-level medical information from whole-slide images. For accurate cell detection,…

cs.CV2021★ 92 cited

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

Byungseok Roh, JaeWoong Shin, Wuhyun Shin +1

DETR is the first end-to-end object detector using a transformer encoder-decoder architecture and demonstrates competitive performance but low computational efficiency on high reso…

cs.LG2021★ 3 cited

Online Hyperparameter Meta-Learning with Hypergradient Distillation

Hae Beom Lee, Hayeon Lee, Jaewoong Shin +3

Many gradient-based meta-learning methods assume a set of parameters that do not participate in inner-optimization, which can be considered as hyperparameters. Although such hyperp…

cs.LG2021★ 1 cited

Large-Scale Meta-Learning with Continual Trajectory Shifting

Jaewoong Shin, Hae Beom Lee, Boqing Gong +1

Meta-learning of shared initialization parameters has shown to be highly effective in solving few-shot learning tasks. However, extending the framework to many-shot scenarios, whic…

cs.LG2020

MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures

Jeongun Ryu, Jaewoong Shin, Hae Beom Lee +1

Regularization and transfer learning are two popular techniques to enhance generalization on unseen data, which is a fundamental problem of machine learning. Regularization techniq…