11 papers
High-Quality and Efficient Turbulence Mitigation with Events
Xiaoran Zhang, Jian Ding, Yuxing Duan +4
Turbulence mitigation (TM) is highly ill-posed due to the stochastic nature of atmospheric turbulence. Most methods rely on multiple frames recorded by conventional cameras to capt…
NEC-Diff: Noise-Robust Event-RAW Complementary Diffusion for Seeing Motion in Extreme Darkness
Haoyue Liu, Jinghan Xu, Luxin Feng +4
High-quality imaging of dynamic scenes in extremely low-light conditions is highly challenging. Photon scarcity induces severe noise and texture loss, causing significant image deg…
Cog2Gen3D: Sculpturing 3D Semantic-Geometric Cognition for 3D Generation
Haonan Wang, Hanyu Zhou, Haoyue Liu +2
Generative models have achieved success in producing semantically plausible 2D images, but it remains challenging in 3D generation due to the absence of spatial geometry constraint…
Adapting Depth Anything to Adverse Imaging Conditions with Events
Shihan Peng, Yuyang Xiong, Hanyu Zhou +5
Robust depth estimation under dynamic and adverse lighting conditions is essential for robotic systems. Currently, depth foundation models, such as Depth Anything, achieve great su…
4D-VGGT: A General Foundation Model with SpatioTemporal Awareness for Dynamic Scene Geometry Estimation
Haonan Wang, Hanyu Zhou, Haoyue Liu +1
We investigate a challenging task of dynamic scene geometry estimation, which requires representing both spatial and temporal features. Typically, existing methods align the two fe…
Injecting Frame-Event Complementary Fusion into Diffusion for Optical Flow in Challenging Scenes
Haonan Wang, Hanyu Zhou, Haoyue Liu +1
Optical flow estimation has achieved promising results in conventional scenes but faces challenges in high-speed and low-light scenes, which suffer from motion blur and insufficien…