6 papers · 1 filter
ExpoCM: Exposure-Aware One-Step Generative Single-Image HDR Reconstruction
Aoyu Liu, Zhen Liu, Ziyi Wang +3
Single-image HDR reconstruction aims to recover high dynamic range radiance from a single low dynamic range (LDR) input, but remains highly ill-posed due to detail saturation in ov…
AnyView: Synthesizing Any Novel View in Dynamic Scenes
Basile Van Hoorick, Dian Chen, Shun Iwase +7
Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consistency in highly dynamic real-world…
OmniShape: Zero-Shot Multi-Hypothesis Shape and Pose Estimation in the Real World
Katherine Liu, Sergey Zakharov, Dian Chen +4
We would like to estimate the pose and full shape of an object from a single observation, without assuming known 3D model or category. In this work, we propose OmniShape, the first…
GTR: Gaussian Splatting Tracking and Reconstruction of Unknown Objects Based on Appearance and Geometric Complexity
Takuya Ikeda, Sergey Zakharov, Muhammad Zubair Irshad +8
We present a novel method for 6-DoF object tracking and high-quality 3D reconstruction from monocular RGBD video. Existing methods, while achieving impressive results, often strugg…
Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion
Vitor Guizilini, Muhammad Zubair Irshad, Dian Chen +2
Current methods for 3D scene reconstruction from sparse posed images employ intermediate 3D representations such as neural fields, voxel grids, or 3D Gaussians, to achieve multi-vi…
Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation
Yinshuang Xu, Dian Chen, Katherine Liu +4
Incorporating inductive bias by embedding geometric entities (such as rays) as input has proven successful in multi-view learning. However, the methods adopting this technique typi…