5 papers
ConvCue: Complementary Visual Inductive Biases for Vision-Language Models
Zixuan Lan, Shichu Sun
Modern vision-language models (VLMs) achieve strong performance across a broad range of multimodal tasks, yet still struggle with visual questions that require fine-grained discrim…
PReD: An LLM-based Foundation Multimodal Model for Electromagnetic Perception, Recognition, and Decision
Zehua Han, Jing Xiao, Yiqi Duan +13
Multimodal Large Language Models have demonstrated powerful cross-modal understanding and reasoning capabilities in general domains. However, in the electromagnetic (EM) domain, th…
LLaVA-UHD v3: Progressive Visual Compression for Efficient Native-Resolution Encoding in MLLMs
Shichu Sun, Yichen Zhang, Haolin Song +6
Visual encoding followed by token condensing has become the standard architectural paradigm in multi-modal large language models (MLLMs). Many recent MLLMs increasingly favor globa…
Boosting Single-domain Generalized Object Detection via Vision-Language Knowledge Interaction
Xiaoran Xu, Jiangang Yang, Wenyue Chong +4
Single-Domain Generalized Object Detection~(S-DGOD) aims to train an object detector on a single source domain while generalizing well to diverse unseen target domains, making it s…
Object Gaussian for Monocular 6D Pose Estimation from Sparse Views
Luqing Luo, Shichu Sun, Jiangang Yang +3
Monocular object pose estimation, as a pivotal task in computer vision and robotics, heavily depends on accurate 2D-3D correspondences, which often demand costly CAD models that ma…