activity
20232025
most citedPAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.GR20253 cited

Virtualized 3D Gaussians: Flexible Cluster-based Level-of-Detail System for Real-Time Rendering of Composed Scenes

Xijie Yang, Linning Xu, Lihan Jiang +2

3D Gaussian Splatting (3DGS) enables the reconstruction of intricate digital 3D assets from multi-view images by leveraging a set of 3D Gaussian primitives for rendering. Its expli…

cs.CV2025

Scene4U: Hierarchical Layered 3D Scene Reconstruction from Single Panoramic Image for Your Immerse Exploration

Zilong Huang, Jun He, Junyan Ye +4

The reconstruction of immersive and realistic 3D scenes holds significant practical importance in various fields of computer vision and computer graphics. Typically, immersive and…

cs.CV2024

Horizon-GS: Unified 3D Gaussian Splatting for Large-Scale Aerial-to-Ground Scenes

Lihan Jiang, Kerui Ren, Mulin Yu +6

Seamless integration of both aerial and street view images remains a significant challenge in neural scene reconstruction and rendering. Existing methods predominantly focus on sin…

cs.CV20235 cited

PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

Qiang Zhou, Weize Li, Lihan Jiang +4

Object anomaly detection is an important problem in the field of machine vision and has seen remarkable progress recently. However, two significant challenges hinder its research a…

cs.CV2023

MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond

Yixuan Li, Lihan Jiang, Linning Xu +4

Neural radiance fields (NeRF) and its subsequent variants have led to remarkable progress in neural rendering. While most of recent neural rendering works focus on objects and smal…