7 papers
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…
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…
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,…
iHDR: Iterative HDR Imaging with Arbitrary Number of Exposures
Yu Yuan, Yiheng Chi, Xingguang Zhang +1
High dynamic range (HDR) imaging aims to obtain a high-quality HDR image by fusing information from multiple low dynamic range (LDR) images. Numerous learning-based HDR imaging met…