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Fatih Porikli

3 papers indexed

arxivcs.CV2026-07-07

MobileWan: Closing the Quality Gap for Mobile Video Diffusion

Mohsen Ghafoorian, Denis Korzhenkov, Adil Karjauv, Ioannis Lelekas, Noor Fathima, Spyridon Stasis, et al.

Recent advances in video diffusion have been driven by scaling transformer-based architectures to billions of parameters, substantially improving visual fidelity and motion coherence. In contrast, existing mobile video diffusion models remain limited to relatively small parameter…

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arxivcs.ROcs.CV2026-07-03

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

Yunxiao Shi, Hong Cai, Mohammad Ghavamzadeh, Fatih Porikli

End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-modal large language models (MLLMs), researchers have proposed the paradigm of Vision-Language-Action (VLA) models for E2E-AD, wher…

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arxivcs.CV2026-06-27

SciFlow: Semantic Cross Interference for Self-Supervised Optical Flow Domain Generalization

Jamie Menjay Lin, Jisoo Jeong, Hong Cai, Kai Wang, Fatih Porikli

Motions of objects and scenes carry essential intelligence in video understanding, offering rich cues for interpreting dynamic settings and interactions. Due to the cost and scarcity of high-quality annotation or ground truth of pixel-wise optical flow, however, motion estimation…

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