activity
20182026
most citedBundle Adjustment Revisited

15 citations · 60 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

GVGS: Gaussian Visibility-Aware Multi-View Geometry for Accurate Surface Reconstruction

Mai Su, Qihan Yu, Zhongtao Wang +5

3D Gaussian Splatting (3DGS) enables efficient rendering, yet accurate surface reconstruction remains challenging due to unreliable geometric supervision. Existing approaches predo…

cs.GR2025

NRRS: Neural Russian Roulette and Splitting

Haojie Jin, Jierui Ren, Yisong Chen +2

We propose a novel framework for Russian Roulette and Splitting (RRS) tailored to wavefront path tracing, a highly parallel rendering architecture that processes path states in bat…

cs.GR2025

HUG: Hierarchical Urban Gaussian Splatting with Block-Based Reconstruction for Large-Scale Aerial Scenes

Mai Su, Zhongtao Wang, Huishan Au +5

3DGS is an emerging and increasingly popular technology in the field of novel view synthesis. Its highly realistic rendering quality and real-time rendering capabilities make it pr…

cs.CV2025

SAIP-Net: Enhancing Remote Sensing Image Segmentation via Spectral Adaptive Information Propagation

Zhongtao Wang, Xizhe Cao, Yisong Chen +1

Semantic segmentation of remote sensing imagery demands precise spatial boundaries and robust intra-class consistency, challenging conventional hierarchical models. To address limi…

cs.CV2024★ 4 cited

SpecGaussian with Latent Features: A High-quality Modeling of the View-dependent Appearance for 3D Gaussian Splatting

Zhiru Wang, Shiyun Xie, Chengwei Pan +1

Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results.…

cs.CV2021★ 13 cited

AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network

Zizhuang Wei, Qingtian Zhu, Chen Min +2

In this paper, we present a novel recurrent multi-view stereo network based on long short-term memory (LSTM) with adaptive aggregation, namely AA-RMVSNet. We firstly introduce an i…