7 papers
ATSplat: Compact Feed-forward 3D Gaussian Splatting with Adaptive Token Expansion
In Cho, Cho In, Jeonghwan Cho +3
3D Gaussian Splatting (3DGS) achieves high-quality novel-view synthesis by optimizing freely placed primitives in 3D and adaptively densifying them in under-reconstructed regions.…
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,…
Unsupervised Monocular 3D Keypoint Discovery from Multi-View Diffusion Priors
Subin Jeon, In Cho, Junyoung Hong +2
Most existing 3D keypoint estimation methods rely on manual annotations or calibrated multi-view images, both of which are expensive to collect. This paper introduces KeyDiff3D, a…
Seam360GS: Seamless 360° Gaussian Splatting from Real-World Omnidirectional Images
Changha Shin, Woong Oh Cho, Seon Joo Kim
360-degree visual content is widely shared on platforms such as YouTube and plays a central role in virtual reality, robotics, and autonomous navigation. However, consumer-grade du…
ExploreGS: Explorable 3D Scene Reconstruction with Virtual Camera Samplings and Diffusion Priors
Minsu Kim, Subin Jeon, In Cho +2
Recent advances in novel view synthesis (NVS) have enabled real-time rendering with 3D Gaussian Splatting (3DGS). However, existing methods struggle with artifacts and missing regi…
4D Scaffold Gaussian Splatting with Dynamic-Aware Anchor Growing for Efficient and High-Fidelity Dynamic Scene Reconstruction
Woong Oh Cho, In Cho, Seoha Kim +3
Modeling dynamic scenes through 4D Gaussians offers high visual fidelity and fast rendering speeds, but comes with significant storage overhead. Recent approaches mitigate this cos…