2 papers
cs.CV2026
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training
Hongzhi Ruan, Pei Liu, Weiliang Ma +5
Data scaling is fundamental to modern deep learning, and grows increasingly critical as autonomous driving shifts to end-to-end learning. Real-world driving data is expensive to an…
cs.GR2025
L3GS: Layered 3D Gaussian Splats for Efficient 3D Scene Delivery
Yi-Zhen Tsai, Xuechen Zhang, Zheng Li +1
Traditional 3D content representations include dense point clouds that consume large amounts of data and hence network bandwidth, while newer representations such as neural radianc…