5 papers
Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
Haoyuan Li, Qihang Cao, Tao Tang +6
Recent progress in spatial reasoning with Multimodal Large Language Models (MLLMs) increasingly leverages geometric priors from 3D encoders. However, most existing integration stra…
Seeing through Imagination: Learning Scene Geometry via Implicit Spatial World Modeling
Meng Cao, Haokun Lin, Haoyuan Li +6
Spatial reasoning, the ability to understand and interpret the 3D structure of the world, is a critical yet underdeveloped capability in Multimodal Large Language Models (MLLMs). C…
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs
Haoyuan Li, Yanpeng Zhou, Yufei Gao +7
Remarkable progress in 2D Vision-Language Models (VLMs) has spurred interest in extending them to 3D settings for tasks like 3D Question Answering, Dense Captioning, and Visual Gro…
EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions
Kai Chen, Yunhao Gou, Runhui Huang +28
GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language…
UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting
Haoyuan Li, Yanpeng Zhou, Tao Tang +5
Recent advancements in multi-modal 3D pre-training methods have shown promising efficacy in learning joint representations of text, images, and point clouds. However, adopting poin…