4 papers · 1 filter
InstaDrive: Instance-Aware Driving World Models for Realistic and Consistent Video Generation
Zhuoran Yang, Xi Guo, Chenjing Ding +3
Autonomous driving relies on robust models trained on high-quality, large-scale multi-view driving videos. While world models offer a cost-effective solution for generating realist…
Physical Informed Driving World Model
Zhuoran Yang, Xi Guo, Chenjing Ding +2
Autonomous driving requires robust perception models trained on high-quality, large-scale multi-view driving videos for tasks like 3D object detection, segmentation and trajectory…
DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation
Wei Wu, Xi Guo, Weixuan Tang +4
Recent advancements in generative models have provided promising solutions for synthesizing realistic driving videos, which are crucial for training autonomous driving perception m…
SGC-VQGAN: Towards Complex Scene Representation via Semantic Guided Clustering Codebook
Chenjing Ding, Chiyu Wang, Boshi Liu +3
Vector quantization (VQ) is a method for deterministically learning features through discrete codebook representations. Recent works have utilized visual tokenizers to discretize v…