3 papers
cs.CV2025
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping
Dongming Wu, Yanping Fu, Saike Huang +8
General robotic grasping systems require accurate object affordance perception in diverse open-world scenarios following human instructions. However, current studies suffer from th…
cs.CV2025
PADriver: Towards Personalized Autonomous Driving
Genghua Kou, Fan Jia, Weixin Mao +7
In this paper, we propose PADriver, a novel closed-loop framework for personalized autonomous driving (PAD). Built upon Multi-modal Large Language Model (MLLM), PADriver takes stre…
cs.CV2024
SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Control
Binyuan Huang, Yuqing Wen, Yucheng Zhao +9
Autonomous driving progress relies on large-scale annotated datasets. In this work, we explore the potential of generative models to produce vast quantities of freely-labeled data…