Khiem Vuong

I'm a PhD student at Carnegie Mellon University (Robotics Institute), where I'm extremely fortunate to be advised by Deva Ramanan and Srinivasa Narasimhan.

Previously, I received my BS in Computer Science from University of Minnesota, working with Stergios Roumeliotis and Hyun Soo Park on VI-SLAM and egocentric scene understanding.

Currently, I'm exploring the intersection of video generative models and 3D/4D reconstruction for building a generative world model.

I'm always happy to chat or collaborate — feel free to reach out at kvuong@andrew.cmu.edu!

Email Resume GitHub Scholar

News

01/2026 I will join Meta Reality Labs as an intern this summer (XR World AI team, working with Peter Kontschieder)!

03/2025 AerialMegaDepth is accepted to CVPR 2025!

02/2025 I will join Apple as an intern this summer (VIO/SLAM team, Video Computer Vision)!

03/2024 WALT3D is accepted to CVPR 2024 as an Oral (top 0.8%)!

10/2023 Toward Planet-Wide Traffic Camera Calibration is accepted to WACV 2024.

Publications

coming soon

FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors

Khiem Vuong, Deva Ramanan*, Srinivasa Narasimhan*

arXiv 2026 (* equal advising)

Coming soon :)

Novel View Synthesis as Video Completion

Qi Wu, Khiem Vuong, Minsik Jeon, Srinivasa Narasimhan, Deva Ramanan

arXiv 2026

paper project

FrameCrafter adapts pretrained video diffusion models for sparse-view novel view synthesis through lightweight architectural changes, achieving state-of-the-art results with minimal training data.

ROADWork: A Dataset and Benchmark for Learning to Recognize, Observe, Analyze and Drive Through Work Zones

Anurag Ghosh, Shen Zheng, Robert Tamburo, Khiem Vuong, Juan Alvarez-Padilla, Hailiang Zhu, Michael Cardei, Nicholas Dunn, Christoph Mertz, Srinivasa G. Narasimhan

ICCV 2025

paper project code

Largest open-source dataset for studying autonomous driving in work zones.

AerialMegaDepth: Learning Aerial-Ground Reconstruction and View Synthesis

Khiem Vuong, Anurag Ghosh, Deva Ramanan*, Srinivasa Narasimhan*, Shubham Tulsiani*

CVPR 2025 (* equal contribution/advising)

paper project 3D viewer code

A scalable data generation framework that combines mesh-renderings with real images, enabling robust 3D reconstruction across extreme viewpoint variations.

WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects under Occlusion

Khiem Vuong*, N Dinesh Reddy*, Robert Tamburo, Srinivasa G. Narasimhan

CVPR 2024 (Oral, top 0.8%) (* equal contribution)

paper project video

Automatically generate realistic training data from time-lapse videos for reconstructing dynamic objects under occlusion.

Toward Planet-Wide Traffic Camera Calibration

Khiem Vuong, Robert Tamburo, Srinivasa G. Narasimhan

WACV 2024

paper project video code

3D scene reconstruction and precise localization of over 100 real-world traffic cameras.

Egocentric Scene Understanding via Multimodal Spatial Rectifier

Tien Do, Khiem Vuong, Hyun Soo Park

CVPR 2022 (Oral, top 4.2%)

paper project video code

Extension of the spatial rectifier to the multi-directional case, applying to depth/surface normal prediction from egocentric view.

Surface Normal Estimation of Tilted Images via Spatial Rectifier

Tien Do, Khiem Vuong, Stergios I. Roumeliotis, Hyun Soo Park

ECCV 2020 (Spotlight, top 3%)

paper project video code

Robust surface normal estimation by spatially rectifying image to the densely distributed orientations.

Deep Multi-view Depth Estimation with Predicted Uncertainty

Tong Ke, Tien Do, Khiem Vuong, Kourosh Sartipi, Stergios I. Roumeliotis

ICRA 2021

paper code

Depth estimation by multiview triangulation, followed by an iterative depth refinement module that preserves estimates with high triangulation confidence.