18 papers
Cross-Modal Attention Calibration for LVLM Hallucination Mitigation
Jiaming Li, Jiacheng Zhang, Zequn Jie +2
Large vision-language models (LVLMs) have shown remarkable capabilities in visual-language understanding. Despite their success, LVLMs still suffer from generating hallucinations i…
X-SAM: From Segment Anything to Any Segmentation
Hao Wang, Limeng Qiao, Zequn Jie +6
Large Language Models (LLMs) demonstrate strong capabilities in broad knowledge representation, yet they are inherently deficient in pixel-level perceptual understanding. Although…
Weakly-Supervised 3D Visual Grounding based on Visual Language Alignment
Xiaoxu Xu, Yitian Yuan, Qiudan Zhang +4
Learning to ground natural language queries to target objects or regions in 3D point clouds is quite essential for 3D scene understanding. Nevertheless, existing 3D visual groundin…
RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving
Zhijian Huang, Chengjian Feng, Feng Yan +5
Large Multimodal Models (LMMs) have demonstrated exceptional comprehension and interpretation capabilities in Autonomous Driving (AD) by incorporating large language models. Despit…
Orthogonal Projection Subspace to Aggregate Online Prior-knowledge for Continual Test-time Adaptation
Jinlong Li, Dong Zhao, Qi Zang +3
Continual Test Time Adaptation (CTTA) is a task that requires a source pre-trained model to continually adapt to new scenarios with changing target distributions. Existing CTTA met…
UniToken: Harmonizing Multimodal Understanding and Generation through Unified Visual Encoding
Yang Jiao, Haibo Qiu, Zequn Jie +4
We introduce UniToken, an auto-regressive generation model that encodes visual inputs through a combination of discrete and continuous representations, enabling seamless integratio…