50 citations · 56 across the 5 of their papers we have counts for
9 papers
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation
Hyojin Park, Jayeon Yoo, Seohyeong Jeong +2
Current state-of-the-art approaches for Semi-supervised Video Object Segmentation (Semi-VOS) propagates information from previous frames to generate segmentation mask for the curre…
TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency Loss
Hyojin Park, Ganesh Venkatesh, Nojun Kwak
Semi-supervised video object segmentation (semi-VOS) is widely used in many applications. This task is tracking class-agnostic objects from a given target mask. For doing this, var…
SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder
Hyojin Park, Lars Lowe Sjösund, YoungJoon Yoo +3
Designing a lightweight and robust portrait segmentation algorithm is an important task for a wide range of face applications. However, the problem has been considered as a subset…
ExtremeC3Net: Extreme Lightweight Portrait Segmentation Networks using Advanced C3-modules
Hyojin Park, Lars Lowe Sjösund, YoungJoon Yoo +2
Designing a lightweight and robust portrait segmentation algorithm is an important task for a wide range of face applications. However, the problem has been considered as a subset…
A Comprehensive Overhaul of Feature Distillation
Byeongho Heo, Jeesoo Kim, Sangdoo Yun +3
We investigate the design aspects of feature distillation methods achieving network compression and propose a novel feature distillation method in which the distillation loss is de…
C3: Concentrated-Comprehensive Convolution and its application to semantic segmentation
Hyojin Park, Youngjoon Yoo, Geonseok Seo +3
One of the practical choices for making a lightweight semantic segmentation model is to combine a depth-wise separable convolution with a dilated convolution. However, the simple c…