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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2024

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…