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most citedGS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting

1 citations · 1 across the 7 of their papers we have counts for

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cs.CV2025

TensoFlow: Tensorial Flow-based Sampler for Inverse Rendering

Chun Gu, Xiaofei Wei, Li Zhang +1

Inverse rendering aims to recover scene geometry, material properties, and lighting from multi-view images. Given the complexity of light-surface interactions, importance sampling…

cs.CV20251 cited

GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting

Junzhe Jiang, Chun Gu, Yurui Chen +1

LiDAR novel view synthesis (NVS) has emerged as a novel task within LiDAR simulation, offering valuable simulated point cloud data from novel viewpoints to aid in autonomous drivin…

cs.CV2024

Reflective Gaussian Splatting

Yuxuan Yao, Zixuan Zeng, Chun Gu +2

Novel view synthesis has experienced significant advancements owing to increasingly capable NeRF- and 3DGS-based methods. However, reflective object reconstruction remains challeng…

cs.CV2024

IRGS: Inter-Reflective Gaussian Splatting with 2D Gaussian Ray Tracing

Chun Gu, Xiaofei Wei, Zixuan Zeng +2

In inverse rendering, accurately modeling visibility and indirect radiance for incident light is essential for capturing secondary effects. Due to the absence of a powerful Gaussia…

cs.CV2024

Tetrahedron Splatting for 3D Generation

Chun Gu, Zeyu Yang, Zijie Pan +2

3D representation is essential to the significant advance of 3D generation with 2D diffusion priors. As a flexible representation, NeRF has been first adopted for 3D representation…

cs.CV2024

Diffusion: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models

Zeyu Yang, Zijie Pan, Chun Gu +1

Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and fi…