5 papers
4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time
Ziqiao Ma, Xuweiyi Chen, Shoubin Yu +10
Can we scale 4D pretraining to learn general space-time representations that reconstruct an object from a few views at some times to any view at any time? We provide an affirmative…
GS4: Generalizable Sparse Splatting Semantic SLAM
Mingqi Jiang, Chanho Kim, Chen Ziwen +1
Traditional SLAM algorithms excel at camera tracking, but typically produce incomplete and low-resolution maps that are not tightly integrated with semantics prediction. Recent wor…
Generating 360° Video is What You Need For a 3D Scene
Zhaoyang Zhang, Yannick Hold-Geoffroy, Miloš Hašan +4
Generating 3D scenes is still a challenging task due to the lack of readily available scene data. Most existing methods only produce partial scenes and provide limited navigational…
MegaSynth: Scaling Up 3D Scene Reconstruction with Synthesized Data
Hanwen Jiang, Zexiang Xu, Desai Xie +11
We propose scaling up 3D scene reconstruction by training with synthesized data. At the core of our work is MegaSynth, a procedurally generated 3D dataset comprising 700K scenes -…
PointRecon: Online Point-based 3D Reconstruction via Ray-based 2D-3D Matching
Chen Ziwen, Zexiang Xu, Li Fuxin
We propose a novel online, point-based 3D reconstruction method from posed monocular RGB videos. Our model maintains a global point cloud representation of the scene, continuously…