5 papers
From Sight to Foresight: Predictive Spatial Reasoning in Vision-Language Models
Feiran Wang, Xiaoqi Wang, Ziwei Li +3
Predicting future spatial states supports collision avoidance and timely decision-making in dynamic environments. However, existing vision-language models (VLMs) and benchmarks for…
From Fragments to Global Maps: Learning Vectorized Map Aggregation with Large Language Models
Ziwei Li, Yi-Tang Chen, Xiaoqi Wang +3
Large-scale vectorized HD maps provide structured road information that is essential for perception, localization, and planning in autonomous driving. Constructing such maps requir…
ViT-Split: Unleashing the Power of Vision Foundation Models via Efficient Splitting Heads
Yifan Li, Xin Li, Tianqin Li +3
Vision foundation models (VFMs) have demonstrated remarkable performance across a wide range of downstream tasks. While several VFM adapters have shown promising results by leverag…
ProSAM: Enhancing the Robustness of SAM-based Visual Reference Segmentation with Probabilistic Prompts
Xiaoqi Wang, Clint Sebastian, Wenbin He +1
The recent advancements in large foundation models have driven the success of open-set image segmentation, a task focused on segmenting objects beyond predefined categories. Among…
DINO-R1: Incentivizing Reasoning Capability in Vision Foundation Models
Chenbin Pan, Wenbin He, Zhengzhong Tu +1
The recent explosive interest in the reasoning capabilities of large language models, such as DeepSeek-R1, has demonstrated remarkable success through reinforcement learning-based…