2 papers
cs.RO2024
Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving
Yupeng Zheng, Pengxuan Yang, Zhongpu Xia +9
The end-to-end autonomous driving paradigm has recently attracted lots of attention due to its scalability. However, existing methods are constrained by the limited scale of real-w…
cs.CV2024
HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM Prompts
Xinyu Liu, Yingqing He, Lanqing Guo +10
The potential for higher-resolution image generation using pretrained diffusion models is immense, yet these models often struggle with issues of object repetition and structural a…