ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2305.06820
  4. Cited By
DeepSTEP -- Deep Learning-Based Spatio-Temporal End-To-End Perception
  for Autonomous Vehicles

DeepSTEP -- Deep Learning-Based Spatio-Temporal End-To-End Perception for Autonomous Vehicles

11 May 2023
Sebastian Huch
Florian Sauerbeck
Johannes Betz
ArXivPDFHTML

Papers citing "DeepSTEP -- Deep Learning-Based Spatio-Temporal End-To-End Perception for Autonomous Vehicles"

3 / 3 papers shown
Title
Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation
  Using Object Detectors and Analyzing Point Clouds at Target-Level
Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-Level
Sebastian Huch
Luca Scalerandi
Esteban Rivera
Markus Lienkamp
3DPC
16
16
0
03 Mar 2023
Loc-NeRF: Monte Carlo Localization using Neural Radiance Fields
Loc-NeRF: Monte Carlo Localization using Neural Radiance Fields
Dominic Maggio
Marcus Abate
J. Shi
C. Mario
Luca Carlone
48
81
0
19 Sep 2022
Delving into the Devils of Bird's-eye-view Perception: A Review,
  Evaluation and Recipe
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe
Hongyang Li
Chonghao Sima
Jifeng Dai
Wenhai Wang
Lewei Lu
...
Xiaosong Jia
Siqian Liu
Jianping Shi
Dahua Lin
Yu Qiao
88
138
0
12 Sep 2022
1