activity
20242026
most citedLidarDM: Generative LiDAR Simulation in a Generated World

2 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

Into the LidarVerse: A Real-Time Unified LiDAR World Model Across Tasks and Sensors

Henry Che, Xuanchi Ren, Sanja Fidler +3

We present LidarVerse, a real-time unified LiDAR world model for sensor simulation across tasks and sensors. Existing LiDAR simulators largely follow one of two complementary parad…

cs.CV2026

Diffusion-guided Generalizable Enhancer for Urban Scene Reconstruction

Henry Che, Jingkang Wang, Yun Chen +3

Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural rendering approaches achieve h…

cs.CV2025

SceneDiff: A Benchmark and Method for Multiview Object Change Detection

Yuqun Wu, Chih-hao Lin, Henry Che +4

We investigate the problem of identifying objects that have been added, removed, or moved between a pair of captures (images or videos) of the same scene at different times. Accura…

cs.CV2025

Flux4D: Flow-based Unsupervised 4D Reconstruction

Jingkang Wang, Henry Che, Yun Chen +4

Reconstructing large-scale dynamic scenes from visual observations is a fundamental challenge in computer vision, with critical implications for robotics and autonomous systems. Wh…

cs.CV2024★ 2 cited

LidarDM: Generative LiDAR Simulation in a Generated World

Vlas Zyrianov, Henry Che, Zhijian Liu +1

We present LidarDM, a novel LiDAR generative model capable of producing realistic, layout-aware, physically plausible, and temporally coherent LiDAR videos. LidarDM stands out with…