2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CV2024
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…
cs.CV2023
MapPrior: Bird's-Eye View Map Layout Estimation with Generative Models
Xiyue Zhu, Vlas Zyrianov, Zhijian Liu +1
Despite tremendous advancements in bird's-eye view (BEV) perception, existing models fall short in generating realistic and coherent semantic map layouts, and they fail to account…
cs.CV2022★ 2 cited
Learning to Generate Realistic LiDAR Point Clouds
Vlas Zyrianov, Xiyue Zhu, Shenlong Wang
We present LiDARGen, a novel, effective, and controllable generative model that produces realistic LiDAR point cloud sensory readings. Our method leverages the powerful score-match…