5 papers
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…
FrozenDrive: Zero-Shot Text-Guided Driving Scene Generation and Data Augmentation with Parameter-Free Frozen Diffusion Model
Yuhwan Jeong, Hyeonseong Kim, Daehyun We +5
Synthetic data for autonomous driving is surging, powered by diffusion models that promise scalable scene generation. Yet key obstacles remain, as enforcing multi-view and temporal…
CXR-LT 2026 Challenge: Projection-Aware Multi-Label and Zero-Shot Chest X-Ray Classification
Juno Cho, Dohui Kim, Mingeon Kim +3
This challenge tackles multi-label classification for known chest X-ray (CXR) lesions and zero-shot classification for unseen ones. To handle diverse CXR projections, we integrate…
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…
GMT: Enhancing Generalizable Neural Rendering via Geometry-Driven Multi-Reference Texture Transfer
Youngho Yoon, Hyun-Kurl Jang, Kuk-Jin Yoon
Novel view synthesis (NVS) aims to generate images at arbitrary viewpoints using multi-view images, and recent insights from neural radiance fields (NeRF) have contributed to remar…