most citedDigging into Depth Priors for Outdoor Neural Radiance Fields

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

HO-Gaussian: Hybrid Optimization of 3D Gaussian Splatting for Urban Scenes

Zhuopeng Li, Yilin Zhang, Chenming Wu +2

The rapid growth of 3D Gaussian Splatting (3DGS) has revolutionized neural rendering, enabling real-time production of high-quality renderings. However, the previous 3DGS-based met…

cs.CV20241 cited

GVA: Reconstructing Vivid 3D Gaussian Avatars from Monocular Videos

Xinqi Liu, Chenming Wu, Jialun Liu +6

In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA). Our innovation lies in addressing the intrica…

cs.CV20232 cited

Digging into Depth Priors for Outdoor Neural Radiance Fields

Chen Wang, Jiadai Sun, Lina Liu +5

Neural Radiance Fields (NeRF) have demonstrated impressive performance in vision and graphics tasks, such as novel view synthesis and immersive reality. However, the shape-radiance…

cs.CV2023

MapNeRF: Incorporating Map Priors into Neural Radiance Fields for Driving View Simulation

Chenming Wu, Jiadai Sun, Zhelun Shen +1

Simulating camera sensors is a crucial task in autonomous driving. Although neural radiance fields are exceptional at synthesizing photorealistic views in driving simulations, they…

cs.RO2023

Boosting Feedback Efficiency of Interactive Reinforcement Learning by Adaptive Learning from Scores

Shukai Liu, Chenming Wu, Ying Li +1

Interactive reinforcement learning has shown promise in learning complex robotic tasks. However, the process can be human-intensive due to the requirement of a large amount of inte…