4 papers
DINOde: Continuous Vision-Text Alignment for Open-Vocabulary Semantic Segmentation
Sung-Hoon Yoon, Hoyong Kwon, Changgyoon Oh +1
Open-vocabulary semantic segmentation (OVSS) leverages textual semantics to segment objects beyond predefined categories. While the self-supervised model DINOv3 provides strong str…
Multimodal Distribution Matching for Vision-Language Dataset Distillation
Jongoh Jeong, Hoyong Kwon, Minseok Kim +1
Dataset distillation compresses large training sets into compact synthetic datasets while preserving downstream performance. As modern systems increasingly operate on paired vision…
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…