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20242026
most citedInstantSplat: Sparse-view Gaussian Splatting in Seconds

9 citations · 14 across the 14 of their papers we have counts for

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Showing 2024 · cs.CVShow all

9 papers · 2 filters

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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,…