12 papers
ACA-GS: Adaptive-Capacity Anchored Gaussian Splatting for Compact Dynamic Radiance Fields
Seunghyeon Song, Joo Chan Lee, Chanung Park +4
Recent advances in 4D Gaussian Splatting (4DGS) enable high-fidelity, real-time spatiotemporal rendering, but expose a fundamental trade-off between motion expressiveness and stora…
NoDrift3R: Raymap-Guided Coupling for Drift-Robust Unposed Feed-Forward 3D Reconstruction
Xiangyu Sun, Liu Liu, Seungkwon Yang +4
Pose-Free Feed-forward 3D Gaussian Splatting (3DGS) has recently emerged as a powerful paradigm for fast scene reconstruction. However, its performance degrades significantly in lo…
Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views
Mijin Yoo, In Cho, Subin Jeon +3
A 3D scene is understood through its objects, not the primitives that compose them. Yet feed-forward reconstruction methods output dense, unstructured sets of points or Gaussians,…
ILV: Iterative Latent Volumes for Fast and Accurate Sparse-View CT Reconstruction
Seungryong Lee, Woojeong Baek, Joosang Lee +1
A long-term goal in CT imaging is to achieve fast and accurate 3D reconstruction from sparse-view projections, thereby reducing radiation exposure, lowering system cost, and enabli…
iLRM: An Iterative Large 3D Reconstruction Model
Gyeongjin Kang, Seungtae Nam, Seungkwon Yang +4
Feed-forward 3D modeling has emerged as a promising approach for rapid and high-quality 3D reconstruction. In particular, directly generating explicit 3D representations, such as 3…
Uni3R: Unified 3D Reconstruction and Semantic Understanding via Generalizable Gaussian Splatting from Unposed Multi-View Images
Xiangyu Sun, Haoyi Jiang, Liu Liu +8
Reconstructing and semantically interpreting 3D scenes from sparse 2D views remains a fundamental challenge in computer vision. Conventional methods often decouple semantic underst…