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20232025
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cs.CV2025

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…

cs.CV2025

SplArt: Articulation Estimation and Part-Level Reconstruction with 3D Gaussian Splatting

Shengjie Lin, Jiading Fang, Muhammad Zubair Irshad +4

Reconstructing articulated objects prevalent in daily environments is crucial for applications in augmented/virtual reality and robotics. However, existing methods face scalability…

cs.CV2025

FastMap: Revisiting Structure from Motion through First-Order Optimization

Jiahao Li, Haochen Wang, Muhammad Zubair Irshad +4

We propose FastMap, a new global structure from motion method focused on speed and simplicity. Previous methods like COLMAP and GLOMAP are able to estimate high-precision camera po…

cs.CV2025

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…

cs.CV2024

Transcrib3D: 3D Referring Expression Resolution through Large Language Models

Jiading Fang, Xiangshan Tan, Shengjie Lin +6

If robots are to work effectively alongside people, they must be able to interpret natural language references to objects in their 3D environment. Understanding 3D referring expres…