1 citations · 1 across the 8 of their papers we have counts for
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AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World
Zhongqiang Song, Guanying Chen, Yuqi Zhang +6
This paper addresses the problem of monocular metric depth estimation in aerial UAV imagery. Although recent data-driven methods have achieved remarkable progress in ground-level s…
UniPR: Unified Object-level Real-to-Sim Perception and Reconstruction from a Single Stereo Pair
Chuanrui Zhang, Yingshuang Zou, ZhengXian Wu +3
Perceiving and reconstructing objects from images are critical for real-to-sim transfer tasks, which are widely used in the robotics community. Existing methods rely on multiple su…
MEGS: Memory-Efficient Gaussian Splatting via Spherical Gaussians and Unified Pruning
Jiarui Chen, Yikeng Chen, Yingshuang Zou +5
3D Gaussian Splatting (3DGS) has emerged as a dominant novel-view synthesis technique, but its high memory consumption severely limits its applicability on edge devices. A growing…
DiST-4D: Disentangled Spatiotemporal Diffusion with Metric Depth for 4D Driving Scene Generation
Jiazhe Guo, Yikang Ding, Xiwu Chen +8
Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-sce…
MuDG: Taming Multi-modal Diffusion with Gaussian Splatting for Urban Scene Reconstruction
Yingshuang Zou, Yikang Ding, Chuanrui Zhang +6
Recent breakthroughs in radiance fields have significantly advanced 3D scene reconstruction and novel view synthesis (NVS) in autonomous driving. Nevertheless, critical limitations…
SLGaussian: Fast Language Gaussian Splatting in Sparse Views
Kangjie Chen, BingQuan Dai, Minghan Qin +4
3D semantic field learning is crucial for applications like autonomous navigation, AR/VR, and robotics, where accurate comprehension of 3D scenes from limited viewpoints is essenti…
UniScene: Unified Occupancy-centric Driving Scene Generation
Bohan Li, Jiazhe Guo, Hongsi Liu +14
Generating high-fidelity, controllable, and annotated training data is critical for autonomous driving. Existing methods typically generate a single data form directly from a coars…
TranSplat: Generalizable 3D Gaussian Splatting from Sparse Multi-View Images with Transformers
Chuanrui Zhang, Yingshuang Zou, Zhuoling Li +2
Compared with previous 3D reconstruction methods like Nerf, recent Generalizable 3D Gaussian Splatting (G-3DGS) methods demonstrate impressive efficiency even in the sparse-view se…
MDepth: Self-supervised Two-Frame Multi-camera Metric Depth Estimation
Yingshuang Zou, Yikang Ding, Xi Qiu +2
This paper presents a novel self-supervised two-frame multi-camera metric depth estimation network, termed MDepth, which is designed to predict reliable scale-aware surroundi…