A platform using flow matching for real-world image generation and an adversarial policy creates challenging corner cases to evaluate end-to-end autonomous driving models like UniAD and VAD, showing performance degradation.
Fast ode-based sampling for diffusion models in around 5 steps,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2025 2verdicts
UNVERDICTED 2representative citing papers
An I²SB diffusion model for CT FOV extension delivers RMSE of 49.8 HU on simulated data and 152.0 HU on real data with 0.19 s per-slice inference, over 700 times faster than cDDPM.
citing papers explorer
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Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
A platform using flow matching for real-world image generation and an adversarial policy creates challenging corner cases to evaluate end-to-end autonomous driving models like UniAD and VAD, showing performance degradation.
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Efficient Image-to-Image Schr\"odinger Bridge for CT Field of View Extension
An I²SB diffusion model for CT FOV extension delivers RMSE of 49.8 HU on simulated data and 152.0 HU on real data with 0.19 s per-slice inference, over 700 times faster than cDDPM.