4 papers
Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing
Xinjie Zhang, Peng Zhang, Shicheng Zheng +21
Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to…
GS-Marker: Generalizable and Robust Watermarking for 3D Gaussian Splatting
Lijiang Li, Jinglu Wang, Xiang Ming +1
In the Generative AI era, safeguarding 3D models has become increasingly urgent. While invisible watermarking is well-established for 2D images with encoder-decoder frameworks, gen…
StreamGS: Online Generalizable Gaussian Splatting Reconstruction for Unposed Image Streams
Yang LI, Jinglu Wang, Lei Chu +4
The advent of 3D Gaussian Splatting (3DGS) has advanced 3D scene reconstruction and novel view synthesis. With the growing interest of interactive applications that need immediate…
UVRM: A Scalable 3D Reconstruction Model from Unposed Videos
Shiu-hong Kao, Xiao Li, Jinglu Wang +4
Large Reconstruction Models (LRMs) have recently become a popular method for creating 3D foundational models. Training 3D reconstruction models with 2D visual data traditionally re…