6 papers · 1 filter
Topology-Aware Representation Alignment for Semi-Supervised Vision-Language Learning
Junwon You, Mihyun Jang, Sangwoo Mo +1
Vision-language models have shown strong performance, but they often generalize poorly to specialized domains. While semi-supervised vision-language learning mitigates this limitat…
Multimodal Dataset Distillation Made Simple by Prototype-Guided Data Synthesis
Junhyeok Choi, Sangwoo Mo, Minwoo Chae
Recent advances in multimodal learning have achieved remarkable success across diverse vision-language tasks. However, such progress heavily relies on large-scale image-text datase…
Aligning Forest and Trees in Images & Long Captions for Visually Grounded Understanding
Byeongju Woo, Zilin Wang, Byeonghyun Pak +2
Vision-language models such as CLIP often struggle to faithfully understand long, detail-rich captions, relying on dominant scene cues while overlooking fine-grained visual evidenc…
SHED Light on Segmentation for Dense Prediction
Seung Hyun Lee, Sangwoo Mo, Stella X. Yu
Dense prediction infers per-pixel values from a single image and is fundamental to 3D perception and robotics. Although real-world scenes exhibit strong structure, existing methods…
Open Ad-hoc Categorization with Contextualized Feature Learning
Zilin Wang, Sangwoo Mo, Stella X. Yu +2
Adaptive categorization of visual scenes is essential for AI agents to handle changing tasks. Unlike fixed common categories for plants or animals, ad-hoc categories are created dy…
Learning Hierarchical Image Segmentation For Recognition and By Recognition
Tsung-Wei Ke, Sangwoo Mo, Stella X. Yu
Large vision and language models learned directly through image-text associations often lack detailed visual substantiation, whereas image segmentation tasks are treated separately…