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20242026
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cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…