9 citations · 14 across the 14 of their papers we have counts for
10 papers · 1 filter
STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes
Jiawei Yang, Jiahui Huang, Yuxiao Chen +10
We present STORM, a spatio-temporal reconstruction model designed for reconstructing dynamic outdoor scenes from sparse observations. Existing dynamic reconstruction methods often…
LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation Models
Ziqi Lu, Heng Yang, Danfei Xu +4
Emerging 3D geometric foundation models, such as DUSt3R, offer a promising approach for in-the-wild 3D vision tasks. However, due to the high-dimensional nature of the problem spac…
Extrapolated Urban View Synthesis Benchmark
Xiangyu Han, Zhen Jia, Boyi Li +8
Photorealistic simulators are essential for the training and evaluation of vision-centric autonomous vehicles (AVs). At their core is Novel View Synthesis (NVS), a crucial capabili…
Large Spatial Model: End-to-end Unposed Images to Semantic 3D
Zhiwen Fan, Jian Zhang, Wenyan Cong +10
Reconstructing and understanding 3D structures from a limited number of images is a well-established problem in computer vision. Traditional methods usually break this task into mu…
Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving
Ran Tian, Boyi Li, Xinshuo Weng +5
The autonomous driving industry is increasingly adopting end-to-end learning from sensory inputs to minimize human biases in system design. Traditional end-to-end driving models, h…
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features
Letian Wang, Seung Wook Kim, Jiawei Yang +7
We propose DistillNeRF, a self-supervised learning framework addressing the challenge of understanding 3D environments from limited 2D observations in outdoor autonomous driving sc…
Memorize What Matters: Emergent Scene Decomposition from Multitraverse
Yiming Li, Zehong Wang, Yue Wang +5
Humans naturally retain memories of permanent elements, while ephemeral moments often slip through the cracks of memory. This selective retention is crucial for robotic perception,…
Language-Image Models with 3D Understanding
Jang Hyun Cho, Boris Ivanovic, Yulong Cao +8
Multi-modal large language models (MLLMs) have shown incredible capabilities in a variety of 2D vision and language tasks. We extend MLLMs' perceptual capabilities to ground and re…
InstantSplat: Sparse-view Gaussian Splatting in Seconds
Zhiwen Fan, Wenyan Cong, Kairun Wen +9
While neural 3D reconstruction has advanced substantially, its performance significantly degrades with sparse-view data, which limits its broader applicability, since SfM is often…
Q-SLAM: Quadric Representations for Monocular SLAM
Chensheng Peng, Chenfeng Xu, Yue Wang +6
In this paper, we reimagine volumetric representations through the lens of quadrics. We posit that rigid scene components can be effectively decomposed into quadric surfaces. Lever…