6 papers · 1 filter
Preference-Guided Adaptation for Open-Vocabulary Semantic Segmentation via Prompt Disagreement
Hyun-Kurl Jang, Jihun Kim, Kuk-Jin Yoon
Open-vocabulary semantic segmentation (OVSS) enables pixel-level prediction over arbitrary text-specified vocabularies and has shown strong generalization on common benchmarks. How…
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…
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…