activity
20232026
most citedMoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation

4 citations · 12 across the 12 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023

Density-invariant Features for Distant Point Cloud Registration

Quan Liu, Hongzi Zhu, Yunsong Zhou +3

Registration of distant outdoor LiDAR point clouds is crucial to extending the 3D vision of collaborative autonomous vehicles, and yet is challenging due to small overlapping area…

cs.DC2023

DistSim: A performance model of large-scale hybrid distributed DNN training

Guandong Lu, Runzhe Chen, Yakai Wang +8

With the ever-increasing computational demand of DNN training workloads, distributed training has been widely adopted. A combination of data, model and pipeline parallelism strateg…

cs.CV2023

APR: Online Distant Point Cloud Registration Through Aggregated Point Cloud Reconstruction

Quan Liu, Yunsong Zhou, Hongzi Zhu +2

For many driving safety applications, it is of great importance to accurately register LiDAR point clouds generated on distant moving vehicles. However, such point clouds have extr…

cs.CV2023★ 4 cited

MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation

Yunsong Zhou, Quan Liu, Hongzi Zhu +3

Monocular 3D object detection (Mono3D) in mobile settings (e.g., on a vehicle, a drone, or a robot) is an important yet challenging task. Due to the near-far disparity phenomenon o…

cs.CV2023★ 2 cited

MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer

Yunsong Zhou, Hongzi Zhu, Quan Liu +2

Mobile monocular 3D object detection (Mono3D) (e.g., on a vehicle, a drone, or a robot) is an important yet challenging task. Existing transformer-based offline Mono3D models adopt…