1 citations · 1 across the 12 of their papers we have counts for
12 papers · 1 filter
From Coordinates to Candidate Regions: Temporal Change Localization via Region Selection in Remote Sensing Multimodal LLMs
Juwan Chung, Sungjune Park, Yeongyun Kim +1
Remote sensing multimodal large language models (RS-MLLMs) have advanced scene understanding and visual question answering over satellite imagery, yet localizing specific objects o…
PRISM: Predictive Recomposition via Semantic Latent Decomposition for View-invariant Video Representation Learning
Youngchae Chee, Hosu Lee, Sungjune Park +2
Cross-view video representation learning aims to capture viewpoint-invariant action semantics despite substantial appearance changes across egocentric and exocentric videos. Howeve…
Robust Grounding with MLLMs Against Occlusion and Small Objects via Language-Guided Semantic Cues
Beomchan Park, Seongho Kim, Hyunjun Kim +2
While Multimodal Large Language Models (MLLMs) have enhanced grounding capabilities in general scenes, their robustness in crowded scenes remains underexplored. Crowded scenes enta…
Video-Oasis: Rethinking Evaluation of Video Understanding
Geuntaek Lim, Sungjune Park, Jaeyun Lee +5
The inherent complexity of video understanding makes it difficult to determine whether Video-LLM benchmark performance stems from visual perception, linguistic reasoning, or knowle…
Robust Egocentric Visual Attention Prediction Through Language-guided Scene Context-aware Learning
Sungjune Park, Hongda Mao, Qingshuang Chen +2
As the demand for analyzing egocentric videos grows, egocentric visual attention prediction, anticipating where a camera wearer will attend, has garnered increasing attention. Howe…
GCAgent: Long-Video Understanding via Schematic and Narrative Episodic Memory
Jeong Hun Yeo, Sangyun Chung, Sungjune Park +3
Long-video understanding remains a significant challenge for Multimodal Large Language Models (MLLMs) due to inherent token limitations and the complexity of capturing long-term te…
Towards Inclusive Communication: A Unified Framework for Generating Spoken Language from Sign, Lip, and Audio
Jeong Hun Yeo, Hyeongseop Rha, Sungjune Park +2
Audio is the primary modality for human communication and has driven the success of Automatic Speech Recognition (ASR) technologies. However, such audio-centric systems inherently…
Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modeling
Sungjune Park, Yeongyun Kim, Se Yeon Kim +1
Large Vision and Language Models (LVLMs) have shown strong performance across various vision-language tasks in natural image domains. However, their application to remote sensing (…
Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images
Sungjune Park, Hyunjun Kim, Beomchan Park +1
Despite recent advancements in computer vision research, object detection in aerial images still suffers from several challenges. One primary challenge to be mitigated is the prese…
DIP-R1: Deep Inspection and Perception with RL Looking Through and Understanding Complex Scenes
Sungjune Park, Hyunjun Kim, Junho Kim +2
MLLMs have demonstrated significant visual understanding capabilities, yet their fine-grained visual perception in complex real-world scenarios, such as densely crowded public area…
Robust Pedestrian Detection via Constructing Versatile Pedestrian Knowledge Bank
Sungjune Park, Hyunjun Kim, Yong Man Ro
Pedestrian detection is a crucial field of computer vision research which can be adopted in various real-world applications (e.g., self-driving systems). However, despite noticeabl…
Integrating Language-Derived Appearance Elements with Visual Cues in Pedestrian Detection
Sungjune Park, Hyunjun Kim, Yong Man Ro
Large language models (LLMs) have shown their capabilities in understanding contextual and semantic information regarding knowledge of instance appearances. In this paper, we intro…