74 citations · 196 across the 26 of their papers we have counts for
4 papers · 1 filter
GRIN: Zero-Shot Metric Depth with Pixel-Level Diffusion
Vitor Guizilini, Pavel Tokmakov, Achal Dave +1
3D reconstruction from a single image is a long-standing problem in computer vision. Learning-based methods address its inherent scale ambiguity by leveraging increasingly large la…
Incorporating dense metric depth into neural 3D representations for view synthesis and relighting
Arkadeep Narayan Chaudhury, Igor Vasiljevic, Sergey Zakharov +4
Synthesizing accurate geometry and photo-realistic appearance of small scenes is an active area of research with compelling use cases in gaming, virtual reality, robotic-manipulati…
Self-Supervised Geometry-Guided Initialization for Robust Monocular Visual Odometry
Takayuki Kanai, Igor Vasiljevic, Vitor Guizilini +1
Monocular visual odometry is a key technology in various autonomous systems. Traditional feature-based methods suffer from failures due to poor lighting, insufficient texture, and…
Towards Realistic Scene Generation with LiDAR Diffusion Models
Haoxi Ran, Vitor Guizilini, Yue Wang
Diffusion models (DMs) excel in photo-realistic image synthesis, but their adaptation to LiDAR scene generation poses a substantial hurdle. This is primarily because DMs operating…