10 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…
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
Generating procedural synthetic data for multi-view stereo (MVS) usually requires writing complex rules to match the realism of curated datasets. We demonstrate that we can generat…
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…
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…
Seeing and Seeing Through the Glass: Real and Synthetic Data for Multi-Layer Depth Estimation
Hongyu Wen, Yiming Zuo, Venkat Subramanian +2
Transparent objects are common in daily life, and understanding their multi-layer depth information -- perceiving both the transparent surface and the objects behind it -- is cruci…
OMNI-DC: Highly Robust Depth Completion with Multiresolution Depth Integration
Yiming Zuo, Willow Yang, Zeyu Ma +1
Depth completion (DC) aims to predict a dense depth map from an RGB image and a sparse depth map. Existing DC methods generalize poorly to new datasets or unseen sparse depth patte…
Towards Foundation Models for 3D Vision: How Close Are We?
Yiming Zuo, Karhan Kayan, Maggie Wang +3
Building a foundation model for 3D vision is a complex challenge that remains unsolved. Towards that goal, it is important to understand the 3D reasoning capabilities of current mo…
OGNI-DC: Robust Depth Completion with Optimization-Guided Neural Iterations
Yiming Zuo, Jia Deng
Depth completion is the task of generating a dense depth map given an image and a sparse depth map as inputs. It has important applications in various downstream tasks. In this pap…