RESEARCH PAPERYear 2024

Generalized Predictive Model for Autonomous Driving

Jiazhi Yang; Shenyuan Gao; Yihang Qiu; Li Chen; Tianyu Li; Bo Dai; Kashyap Chitta; Penghao Wu; Jia Zeng; Ping Luo; Jun Zhang; Andreas Geiger; Yu Qiao; Hongyang Li

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Major category: WAMs
Quadrant: Not applicable
Architecture: Not applicable
Prediction paradigm: Not applicable
Subcategories: Neural world simulators
Source review status: Verified from primary sources

Category review. GenAD learns driving future-video representations and supports a separately trained trajectory planner reading its frozen encoder features. It is a task-specific predictive-model/control method with a planning extension, while its SDXL/CLIP/autoencoder are the reusable components. Reading evidence

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BibTeX

@inproceedings{opendv,
  author       = {Jiazhi Yang and
                  Shenyuan Gao and
                  Yihang Qiu and
                  Li Chen and
                  Tianyu Li and
                  Bo Dai and
                  Kashyap Chitta and
                  Penghao Wu and
                  Jia Zeng and
                  Ping Luo and
                  Jun Zhang and
                  Andreas Geiger and
                  Yu Qiao and
                  Hongyang Li},
  title        = {Generalized Predictive Model for Autonomous Driving},
  booktitle    = {CVPR},
  pages        = {14662--14672},
  year         = {2024},
}

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