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Wenkang Qin

3 accepted papers

2025

ReconDreamer++: Harmonizing Generative and Reconstructive Models for Driving Scene Representation

ICCV 2025poster

Combining reconstruction models with generative models has emerged as a promising paradigm for closed-loop simulation in autonomous driving. For example, ReconDreamer has demonstrated remarkable success in rendering large-scale maneuvers. However, a significant gap remains between the generated data…

Cited by 0SourcePDFScholar
2025

ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration

CVPR 2025poster

Closed-loop simulation is crucial for end-to-end autonomous driving. Existing sensor simulation methods (e.g., NeRF and 3DGS) reconstruct driving scenes based on conditions that closely mirror training data distributions. However, these methods struggle with rendering novel trajectories, such as lan…

Cited by 11SourcePDFScholar
2025

WonderTurbo: Generating Interactive 3D World in 0.72 Seconds

ICCV 2025poster

Interactive 3D generation is gaining momentum and capturing extensive attention for its potential to create immersive virtual experiences. However, a critical challenge in current 3D generation technologies lies in achieving real-time interactivity. To address this issue, we introduce WonderTurbo, t…

Cited by 0SourcePDFScholar