25 citations · 46 across the 13 of their papers we have counts for
15 papers
Instant NuRec: Feed-Forward 3D Gaussian Reconstruction for Driving Scene Simulation
NVIDIA, :, Jiahui Huang +14
3D simulation platforms are critical for autonomous driving because they enable end-to-end policy evaluation, thereby reducing development costs and improving safety. In recent yea…
Asset Harvester: Extracting 3D Assets from Autonomous Driving Logs for Simulation
Tianshi Cao, Jiawei Ren, Yuxuan Zhang +12
Closed-loop simulation is a core component of autonomous vehicle (AV) development, enabling scalable testing, training, and safety validation before real-world deployment. Neural s…
RadarGen: Automotive Radar Point Cloud Generation from Cameras
Tomer Borreda, Fangqiang Ding, Sanja Fidler +2
We present RadarGen, a diffusion model for synthesizing realistic automotive radar point clouds from multi-view camera imagery. RadarGen adapts efficient image-latent diffusion to…
InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models
Yifan Lu, Xuanchi Ren, Jiawei Yang +8
We present InfiniCube, a scalable method for generating unbounded dynamic 3D driving scenes with high fidelity and controllability. Previous methods for scene generation either suf…
Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos
Hanxue Liang, Jiawei Ren, Ashkan Mirzaei +8
Recent advancements in static feed-forward scene reconstruction have demonstrated significant progress in high-quality novel view synthesis. However, these models often struggle wi…
ReMatching Dynamic Reconstruction Flow
Sara Oblak, Despoina Paschalidou, Sanja Fidler +1
Reconstructing a dynamic scene from image inputs is a fundamental computer vision task with many downstream applications. Despite recent advancements, existing approaches still str…
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats
Xuanchi Ren, Yifan Lu, Hanxue Liang +6
We present SCube, a novel method for reconstructing large-scale 3D scenes (geometry, appearance, and semantics) from a sparse set of posed images. Our method encodes reconstructed…
Wolf: Dense Video Captioning with a World Summarization Framework
Boyi Li, Ligeng Zhu, Ran Tian +20
We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is an automated captioning framework that adopts a mixture-of-experts approach, leveraging comp…
fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence
Francis Williams, Jiahui Huang, Jonathan Swartz +9
We present fVDB, a novel GPU-optimized framework for deep learning on large-scale 3D data. fVDB provides a complete set of differentiable primitives to build deep learning architec…
NeRF-XL: Scaling NeRFs with Multiple GPUs
Ruilong Li, Sanja Fidler, Angjoo Kanazawa +1
We present NeRF-XL, a principled method for distributing Neural Radiance Fields (NeRFs) across multiple GPUs, thus enabling the training and rendering of NeRFs with an arbitrarily…
Trajeglish: Traffic Modeling as Next-Token Prediction
Jonah Philion, Xue Bin Peng, Sanja Fidler
A longstanding challenge for self-driving development is simulating dynamic driving scenarios seeded from recorded driving logs. In pursuit of this functionality, we apply tools fr…
XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchies
Xuanchi Ren, Jiahui Huang, Xiaohui Zeng +3
We present XCube (abbreviated as ), a novel generative model for high-resolution sparse 3D voxel grids with arbitrary attributes. Our model can generate millions of…
3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features
Chenfeng Xu, Huan Ling, Sanja Fidler +1
We present 3DiffTection, a state-of-the-art method for 3D object detection from single images, leveraging features from a 3D-aware diffusion model. Annotating large-scale image dat…
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision
Jiawei Yang, Boris Ivanovic, Or Litany +8
We present EmerNeRF, a simple yet powerful approach for learning spatial-temporal representations of dynamic driving scenes. Grounded in neural fields, EmerNeRF simultaneously capt…
Towards Viewpoint Robustness in Bird's Eye View Segmentation
Tzofi Klinghoffer, Jonah Philion, Wenzheng Chen +6
Autonomous vehicles (AV) require that neural networks used for perception be robust to different viewpoints if they are to be deployed across many types of vehicles without the rep…