From the 2 of 8 linked papers with an AI index.
8 papers
TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations
Zikang Xiong, Weixin Li, Zhouchonghao Wu +6
The paper proposes a method to train end-to-end autonomous driving policies without expert demonstrations by pretraining a policy via self‑play in a fast vectorized simulator and t…
TerraZero: Procedural Driving Simulation for Zero-Demonstration Self-Play at Scale
Zhouchonghao Wu, Akshay Rangesh, Weixin Li +5
TerraZero is a procedural driving simulator that enables large-scale, zero‑demonstration self‑play reinforcement learning for autonomous driving, achieving high simulation speed an…
Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution
Tianshuo Xu, Yichen Xie, Depu Meng +5
Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption. This is not simply a capacity p…
LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation
Bo Jiang, Depu Meng, Yihan Hu +3
Modern video generators produce visually compelling clips but still struggle with physical and motion consistency, limiting their use as reliable world simulators. Existing remedie…
R3D2: Realistic 3D Asset Insertion via Diffusion for Autonomous Driving Simulation
William Ljungbergh, Bernardo Taveira, Wenzhao Zheng +8
Validating autonomous driving (AD) systems requires diverse and safety-critical testing, making photorealistic virtual environments essential. Traditional simulation platforms, whi…
SpectralSplat: Appearance-Disentangled Feed-Forward Gaussian Splatting for Driving Scenes
Quentin Herau, Tianshuo Xu, Depu Meng +5
Feed-forward 3D Gaussian Splatting methods have achieved impressive reconstruction quality for autonomous driving scenes, yet they entangle scene geometry with transient appearance…