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20212026
most citedHUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting

2 citations · 5 across the 26 of their papers we have counts for

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Showing 2026 · cs.CVShow all

12 papers · 2 filters

cs.CV2026

Motion- and Gravity-Aware Feedforward 3D Reconstruction

Shiyao Qian, Yuan Ren, Dongfeng Bai

Feed-forward transformer models have recently achieved strong performance in multi-view 3D reconstruction, but they still rely primarily on appearance-based attention and often str…

cs.CV2026

GeoWM: Efficient Direct World Modeling in Explicit Geometry

Mehrdad Noori, Guile Wu, Sam Hosseini +1

Modeling 3D scene geometry and its evolution over time is essential for autonomous driving and robotics. A common paradigm is to use world models to predict future images or latent…

cs.CV2026

GeoComposer: Geometry-Grounded Photographic Composition Instruction

Shuangzhi Li, Qiaoqiao Jia, Xingxin Chen +2

Photographic composition aims to provide visual guidance for improving the framing, viewpoint, and spatial arrangement of an image. Early methods primarily rely on image cropping t…

cs.CV2026

VGGT-Prime: Compute-Adaptive Mixture-of-Heads for Efficient Visual Geometry Transformers

Abteen Arab, Guile Wu, Chengjie Huang +1

Feed-forward visual geometry models such as the Visual Geometry Grounded Transformer (VGGT) have recently enabled direct 3D reconstruction from multi-view images. Despite their pro…

cs.CV2026

Chain of Spatial Thoughts: Modality-Agnostic Spatial Grounding for Vision Language Models

Hunter Schofield, Mohammed Elmahgiubi, Mohammad Mahdavian +4

Spatial understanding is fundamental to embodied intelligence, underpinning applications such as robotic manipulation, embodied navigation, and autonomous driving. Although recent…

cs.CV2026

TurboVGGT: Fast Visual Geometry Reconstruction with Adaptive Alternating Attention

David Huang, Guile Wu, Chengjie Huang +2

Recent feed-forward 3D reconstruction methods, such as visual geometry transformers, have substantially advanced the traditional per-scene optimization paradigm by enabling effecti…

cs.CV2026

UniScale: Unified Scale-Aware 3D Reconstruction for Multi-View Understanding via Prior Injection for Robotic Perception

Mohammad Mahdavian, Gordon Tan, Binbin Xu +3

We present UniScale, a unified, scale-aware multi-view 3D reconstruction framework for robotic applications that flexibly integrates geometric priors through a modular, semanticall…

cs.CV2026

Language and Geometry Grounded Sparse Voxel Representations for Holistic Scene Understanding

Guile Wu, David Huang, Bingbing Liu +1

Existing 3D open-vocabulary scene understanding methods mostly emphasize distilling language features from 2D foundation models into 3D feature fields, but largely overlook the syn…

cs.CV2026

Nighttime Autonomous Driving Scene Reconstruction with Physically-Based Gaussian Splatting

Tae-Kyeong Kim, Xingxin Chen, Guile Wu +3

This paper focuses on scene reconstruction under nighttime conditions in autonomous driving simulation. Recent methods based on Neural Radiance Fields (NeRFs) and 3D Gaussian Splat…

cs.CV2026

FreeFix: Boosting 3D Gaussian Splatting via Fine-Tuning-Free Diffusion Models

Hongyu Zhou, Zisen Shao, Sheng Miao +4

Neural Radiance Fields and 3D Gaussian Splatting have advanced novel view synthesis, yet still rely on dense inputs and often degrade at extrapolated views. Recent approaches lever…

cs.CV2026

EVolSplat4D: Efficient Volume-based Gaussian Splatting for 4D Urban Scene Synthesis

Sheng Miao, Sijin Li, Pan Wang +5

Novel view synthesis (NVS) of static and dynamic urban scenes is essential for autonomous driving simulation, yet existing methods often struggle to balance reconstruction time wit…

cs.CV2026

Spatial4D-Bench: A Versatile 4D Spatial Intelligence Benchmark

Pan Wang, Yang Liu, Guile Wu +23

4D spatial intelligence involves perceiving and processing how objects move or change over time. Humans naturally possess 4D spatial intelligence, supporting a broad spectrum of sp…