3 citations · 3 across the 8 of their papers we have counts for
10 papers · 1 filter
ReCoG: Relational Concept Graph for Training-Free Personalization
Changseon Yu, Hyeokjun Kweon
Training-free personalization adapts a frozen vision-language model (VLM) to recognize user-defined concepts from only a few exemplars by retrieving concept entries at inference ti…
Bootstrapping a 4D LiDAR Annotation Tool from Video Foundation Models
Jihun Kim, Hyun-Kurl Jang, Hyemin Yang +3
Progress in 4D LiDAR segmentation is bottlenecked by data. Assigning temporally consistent labels across sparse point cloud sequences is costly and hard to scale, and every new tas…
Enhanced Seam Segmentation for Automated Welding Robot in Construction Through Transfer Learning: Addressing Limitations of Bilateral Segmentation Network
Keonvin Park, Yong Ann Voeurn, Hyeokjun Kweon +1
Reliable seam segmentation is essential for autonomous robotic welding in construction, where harsh illumination, specular reflections, and thin weld geometries often degrade segme…
Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation
Hyun-Kurl Jang, Jihun Kim, Hyeokjun Kweon +1
Continual Test-Time Adaptation (CTTA) aims to maintain model performance under evolving target domains by adapting online without labeled data. However, practical deployments often…
Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation
Jihun Kim, Hoyong Kwon, Hyeokjun Kweon +1
Fully supervised Video Semantic Segmentation (VSS) relies heavily on densely annotated video data, limiting practical applicability. Alternatively, applying pre-trained Image Seman…
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
Jihun Kim, Hoyong Kwon, Hyeokjun Kweon +2
Interactive segmentation (IS) allows users to iteratively refine object boundaries with minimal cues, such as positive and negative clicks. While the Segment Anything Model (SAM) h…
TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight
Hyun-Kurl Jang, Jihun Kim, Hyeokjun Kweon +1
Semantic Scene Completion (SSC) aims to perform geometric completion and semantic segmentation simultaneously. Despite the promising results achieved by existing studies, the inher…
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event Cameras
Hoonhee Cho, Sung-Hoon Yoon, Hyeokjun Kweon +1
Event cameras excel in capturing high-contrast scenes and dynamic objects, offering a significant advantage over traditional frame-based cameras. Despite active research into lever…
Pixel-wise Deep Image Stitching
Hyeokjun Kweon, Hyeonseong Kim, Yoonsu Kang +3
Image stitching aims at stitching the images taken from different viewpoints into an image with a wider field of view. Existing methods warp the target image to the reference image…
Exploring Pixel-level Self-supervision for Weakly Supervised Semantic Segmentation
Sung-Hoon Yoon, Hyeokjun Kweon, Jaeseok Jeong +3
Existing studies in weakly supervised semantic segmentation (WSSS) have utilized class activation maps (CAMs) to localize the class objects. However, since a classification loss is…