9 papers
InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics
Erich Liang, Caleb Kha-Uong, Chinmaya Saran +5
Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assumption that often fails for re…
Princeton365: A Diverse Dataset with Accurate Camera Pose
Karhan Kayan, Stamatis Alexandropoulos, Rishabh Jain +3
We introduce Princeton365, a large-scale diverse dataset of 365 videos with accurate camera pose. Our dataset bridges the gap between accuracy and data diversity in current SLAM be…
ProcFunc: Function-Oriented Abstractions for Procedural 3D Generation in Python
Alexander Raistrick, Karhan Kayan, Jack Nugent +8
We introduce ProcFunc, a library for Blender-based procedural 3D generation in Python. ProcFunc provides a library of easy-to-use Python functions, which streamline creating, combi…
SimpleProc: Fully Procedural Synthetic Data from Simple Rules for Multi-View Stereo
Zeyu Ma, Alexander Raistrick, Jia Deng
In this paper, we explore the design space of procedural rules for multi-view stereo (MVS). We demonstrate that we can generate effective training data using SimpleProc: a new, ful…
InFlux: A Benchmark for Self-Calibration of Dynamic Intrinsics of Video Cameras
Erich Liang, Roma Bhattacharjee, Sreemanti Dey +8
Accurately tracking camera intrinsics is crucial for achieving 3D understanding from 2D video. However, most 3D algorithms assume that camera intrinsics stay constant throughout a…
Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound
Yuhao Huang, Yueyue Xu, Haoran Dou +4
Congenital uterine anomalies (CUAs) can lead to infertility, miscarriage, preterm birth, and an increased risk of pregnancy complications. Compared to traditional 2D ultrasound (US…