21 citations · 36 across the 5 of their papers we have counts for
5 papers
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation
Seungho Lee, Minhyun Lee, Jongwuk Lee +1
Existing studies in weakly-supervised semantic segmentation (WSSS) using image-level weak supervision have several limitations: sparse object coverage, inaccurate object boundaries…
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets
Junsuk Choe, Seong Joon Oh, Sanghyuk Chun +3
Weakly-supervised object localization (WSOL) has gained popularity over the last years for its promise to train localization models with only image-level labels. Since the seminal…
Evaluating Weakly Supervised Object Localization Methods Right
Junsuk Choe, Seong Joon Oh, Seungho Lee +3
Weakly-supervised object localization (WSOL) has gained popularity over the last years for its promise to train localization models with only image-level labels. Since the seminal…
Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation
Woong Bae, Seungho Lee, Yeha Lee +3
Neural Architecture Search (NAS), a framework which automates the task of designing neural networks, has recently been actively studied in the field of deep learning. However, ther…
Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning
Chen Zhang, Hao Yan, Seungho Lee +1
Multivariate functional data from a complex system are naturally high-dimensional and have complex cross-correlation structure. The complexity of data structure can be observed as…