8 citations · 41 across the 34 of their papers we have counts for
7 papers · 1 filter
Synchronizing Vision and Language: Bidirectional Token-Masking AutoEncoder for Referring Image Segmentation
Minhyeok Lee, Dogyoon Lee, Jungho Lee +4
Referring Image Segmentation (RIS) aims to segment target objects expressed in natural language within a scene at the pixel level. Various recent RIS models have achieved state-of-…
Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
Suhwan Cho, Minhyeok Lee, Jungho Lee +5
Unsupervised video object segmentation aims to detect the most salient object in a video without any external guidance regarding the object. Salient objects often exhibit distincti…
Adaptive Graph Convolution Module for Salient Object Detection
Yongwoo Lee, Minhyeok Lee, Suhwan Cho +1
Salient object detection (SOD) is a task that involves identifying and segmenting the most visually prominent object in an image. Existing solutions can accomplish this use a multi…
Guided Slot Attention for Unsupervised Video Object Segmentation
Minhyeok Lee, Suhwan Cho, Dogyoon Lee +3
Unsupervised video object segmentation aims to segment the most prominent object in a video sequence. However, the existence of complex backgrounds and multiple foreground objects…
Tsanet: Temporal and Scale Alignment for Unsupervised Video Object Segmentation
Seunghoon Lee, Suhwan Cho, Dogyoon Lee +2
Unsupervised Video Object Segmentation (UVOS) refers to the challenging task of segmenting the prominent object in videos without manual guidance. In recent works, two approaches f…
One-Shot Video Inpainting
Sangjin Lee, Suhwan Cho, Sangyoun Lee
Recently, removing objects from videos and filling in the erased regions using deep video inpainting (VI) algorithms has attracted considerable attention. Usually, a video sequence…
Two-stream Decoder Feature Normality Estimating Network for Industrial Anomaly Detection
Chaewon Park, Minhyeok Lee, Suhwan Cho +2
Image reconstruction-based anomaly detection has recently been in the spotlight because of the difficulty of constructing anomaly datasets. These approaches work by learning to mod…