11 citations · 20 across the 6 of their papers we have counts for
8 papers · 1 filter
Correlation Verification for Image Retrieval
Seongwon Lee, Hongje Seong, Suhyeon Lee +1
Geometric verification is considered a de facto solution for the re-ranking task in image retrieval. In this study, we propose a novel image retrieval re-ranking network named Corr…
WildNet: Learning Domain Generalized Semantic Segmentation from the Wild
Suhyeon Lee, Hongje Seong, Seongwon Lee +1
We present a new domain generalized semantic segmentation network named WildNet, which learns domain-generalized features by leveraging a variety of contents and styles from the wi…
Hierarchical Memory Matching Network for Video Object Segmentation
Hongje Seong, Seoung Wug Oh, Joon-Young Lee +3
We present Hierarchical Memory Matching Network (HMMN) for semi-supervised video object segmentation. Based on a recent memory-based method [33], we propose two advanced memory rea…
Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer
Suhyeon Lee, Junhyuk Hyun, Hongje Seong +1
In this paper, we tackle the unsupervised domain adaptation (UDA) for semantic segmentation, which aims to segment the unlabeled real data using labeled synthetic data. The main pr…
3D-DEEP: 3-Dimensional Deep-learning based on elevation patterns forroad scene interpretation
A. Hernández, S. Woo, H. Corrales +4
Road detection and segmentation is a crucial task in computer vision for safe autonomous driving. With this in mind, a new net architecture (3D-DEEP) and its end-to-end training me…
Kernelized Memory Network for Video Object Segmentation
Hongje Seong, Junhyuk Hyun, Euntai Kim
Semi-supervised video object segmentation (VOS) is a task that involves predicting a target object in a video when the ground truth segmentation mask of the target object is given…