24 citations · 30 across the 30 of their papers we have counts for
10 papers · 1 filter
Revealing Multi-View Hallucination in Large Vision-Language Models
Wooje Park, Insu Lee, Soohyun Kim +4
Large vision-language models (LVLMs) are increasingly being applied to multi-view image inputs captured from diverse viewpoints. Despite this growing use, current LVLMs often gener…
Towards Comprehensive Scene Understanding: Integrating First and Third-Person Views for LVLMs
Insu Lee, Wooje Park, Jaeyun Jang +3
Large vision-language models (LVLMs) are increasingly deployed in interactive applications such as virtual and augmented reality, where a first-person (egocentric) view captured by…
Learning Primitive Relations for Compositional Zero-Shot Learning
Insu Lee, Jiseob Kim, Kyuhong Shim +1
Compositional Zero-Shot Learning (CZSL) aims to identify unseen state-object compositions by leveraging knowledge learned from seen compositions. Existing approaches often independ…
Unlocking Transfer Learning for Open-World Few-Shot Recognition
Byeonggeun Kim, Juntae Lee, Kyuhong Shim +1
Few-Shot Open-Set Recognition (FSOSR) targets a critical real-world challenge, aiming to categorize inputs into known categories, termed closed-set classes, while identifying open-…
Role of Sensing and Computer Vision in 6G Wireless Communications
Seungnyun Kim, Jihoon Moon, Jinhong Kim +5
Recently, we are witnessing the remarkable progress and widespread adoption of sensing technologies in autonomous driving, robotics, and metaverse. Considering the rapid advancemen…
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization
Jiyoung Kim, Kyuhong Shim, Insu Lee +1
Unsupervised semantic segmentation (USS) aims to discover and recognize meaningful categories without any labels. For a successful USS, two key abilities are required: 1) informati…
Depth-Relative Self Attention for Monocular Depth Estimation
Kyuhong Shim, Jiyoung Kim, Gusang Lee +1
Monocular depth estimation is very challenging because clues to the exact depth are incomplete in a single RGB image. To overcome the limitation, deep neural networks rely on vario…
Semantic-Preserving Augmentation for Robust Image-Text Retrieval
Sunwoo Kim, Kyuhong Shim, Luong Trung Nguyen +1
Image text retrieval is a task to search for the proper textual descriptions of the visual world and vice versa. One challenge of this task is the vulnerability to input image and…
Vision Transformer-based Feature Extraction for Generalized Zero-Shot Learning
Jiseob Kim, Kyuhong Shim, Junhan Kim +1
Generalized zero-shot learning (GZSL) is a technique to train a deep learning model to identify unseen classes using the image attribute. In this paper, we put forth a new GZSL app…
Semantic Feature Extraction for Generalized Zero-shot Learning
Junhan Kim, Kyuhong Shim, Byonghyo Shim
Generalized zero-shot learning (GZSL) is a technique to train a deep learning model to identify unseen classes using the attribute. In this paper, we put forth a new GZSL technique…