2 citations · 3 across the 5 of their papers we have counts for
6 papers
Context-Preserving Instance-Level Augmentation and Deformable Convolution Networks for SAR Ship Detection
Taeyong Song, Sunok Kim, SungTai Kim +2
Shape deformation of targets in SAR image due to random orientation and partial information loss caused by occlusion of the radar signal, is an essential challenge in SAR ship dete…
Dual Prototypical Contrastive Learning for Few-shot Semantic Segmentation
Hyeongjun Kwon, Somi Jeong, Sunok Kim +1
We address the problem of few-shot semantic segmentation (FSS), which aims to segment novel class objects in a target image with a few annotated samples. Though recent advances hav…
Looking into Your Speech: Learning Cross-modal Affinity for Audio-visual Speech Separation
Jiyoung Lee, Soo-Whan Chung, Sunok Kim +2
In this paper, we address the problem of separating individual speech signals from videos using audio-visual neural processing. Most conventional approaches utilize frame-wise matc…
On the confidence of stereo matching in a deep-learning era: a quantitative evaluation
Matteo Poggi, Seungryong Kim, Fabio Tosi +5
Stereo matching is one of the most popular techniques to estimate dense depth maps by finding the disparity between matching pixels on two, synchronized and rectified images. Along…
Context-Aware Emotion Recognition Networks
Jiyoung Lee, Seungryong Kim, Sunok Kim +2
Traditional techniques for emotion recognition have focused on the facial expression analysis only, thus providing limited ability to encode context that comprehensively represents…
Semantic Attribute Matching Networks
Seungryong Kim, Dongbo Min, Somi Jeong +3
We present semantic attribute matching networks (SAM-Net) for jointly establishing correspondences and transferring attributes across semantically similar images, which intelligent…