6 papers · 1 filter
OptiWorld: Optimal Control for Video World Generation under Physical Constraints
Yu Yuan, Jianhao Yuan, Xijun Wang +4
Video generation models are becoming a scalable form of world models, but they mainly generate plausible motion rather than proactively control or optimize the underlying dynamics.…
SeeU: Seeing the Unseen World via 4D Dynamics-aware Generation
Yu Yuan, Tharindu Wickremasinghe, Zeeshan Nadir +3
Images and videos are discrete 2D projections of the 4D world (3D space + time). Most visual understanding, prediction, and generation operate directly on 2D observations, leading…
NewtonGen: Physics-Consistent and Controllable Text-to-Video Generation via Neural Newtonian Dynamics
Yu Yuan, Xijun Wang, Tharindu Wickremasinghe +3
A primary bottleneck in large-scale text-to-video generation today is physical consistency and controllability. Despite recent advances, state-of-the-art models often produce unrea…
Astrophotography turbulence mitigation via generative models
Joonyeoup Kim, Yu Yuan, Xingguang Zhang +2
Photography is the cornerstone of modern astronomical and space research. However, most astronomical images captured by ground-based telescopes suffer from atmospheric turbulence,…
Personalized Generative Low-light Image Denoising and Enhancement
Xijun Wang, Prateek Chennuri, Dilshan Godaliyadda +5
Modern cameras' performance in low-light conditions remains suboptimal due to fundamental limitations in photon shot noise and sensor read noise. Generative image restoration metho…
Generative Photography: Scene-Consistent Camera Control for Realistic Text-to-Image Synthesis
Yu Yuan, Xijun Wang, Yichen Sheng +3
Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a specific camera setting such as creating differen…