1 citations · 1 across the 9 of their papers we have counts for
10 papers
Diffusion Large Language Models for Visual Speech Recognition
Jeong Hun Yeo, Chae Won Kim, Hyeongseop Rha +1
Existing Visual Speech Recognition (VSR) systems commonly rely on left-to-right autoregressive decoding, which can force premature decisions on visually ambiguous tokens before suf…
STRIDE: When to Speak Meets Sequence Denoising for Streaming Video Understanding
Junho Kim, Hosu Lee, James M. Rehg +2
Recent progress in video large language models (Video-LLMs) has enabled strong offline reasoning over long and complex videos. However, real-world deployments increasingly require…
MAD: Modality-Adaptive Decoding for Mitigating Cross-Modal Hallucinations in Multimodal Large Language Models
Sangyun Chung, Se Yeon Kim, Youngchae Chee +1
Multimodal Large Language Models (MLLMs) suffer from cross-modal hallucinations, where one modality inappropriately influences generation about another, leading to fabricated outpu…
Unified Reinforcement and Imitation Learning for Vision-Language Models
Byung-Kwan Lee, Ryo Hachiuma, Yong Man Ro +2
Vision-Language Models (VLMs) have achieved remarkable progress, yet their large scale often renders them impractical for resource-constrained environments. This paper introduces U…
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…
VLsI: Verbalized Layers-to-Interactions from Large to Small Vision Language Models
Byung-Kwan Lee, Ryo Hachiuma, Yu-Chiang Frank Wang +2
The recent surge in high-quality visual instruction tuning samples from closed-source vision-language models (VLMs) such as GPT-4V has accelerated the release of open-source VLMs a…
Look Every Frame All at Once: Video-Mamba for Efficient Long-form Video Understanding with Multi-Axis Gradient Checkpointing
Hosu Lee, Junho Kim, Hyunjun Kim +1
With the growing scale and complexity of video data, efficiently processing long video sequences poses significant challenges due to the quadratic increase in memory and computatio…
Revisiting Misalignment in Multispectral Pedestrian Detection: A Language-Driven Approach for Cross-modal Alignment Fusion
Taeheon Kim, Sangyun Chung, Youngjoon Yu +1
Multispectral pedestrian detection is a crucial component in various critical applications. However, a significant challenge arises due to the misalignment between these modalities…
Phantom of Latent for Large Language and Vision Models
Byung-Kwan Lee, Sangyun Chung, Chae Won Kim +2
The success of visual instruction tuning has accelerated the development of large language and vision models (LLVMs). Following the scaling laws of instruction-tuned large language…