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Danfei Xu

34 papers hereh-index 3310.1k citations45 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author7
  • middle author24
  • last author3

Across the 34 of 34 papers where every author was matched, so the position is known.

fields
  • cs.RO16
  • cs.CV10
  • cs.AI4
  • cs.LG4
same name
  • Danfei Xu — 17 papers, h 4
  • Danfei Xu — 13 papers, h 5
  • Danfei Xu — 9 papers, h 8
  • Danfei Xu — 9 papers, h 7
  • Danfei Xu — 8 papers, h 8
  • Danfei Xu — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152023
most citedScene Graph Generation by Iterative Message Passing

100 citations · 587 across the 34 of their papers we have counts for

collaborators
Showing 2023 · cs.ROShow all

4 papers · 2 filters

cs.RO2023

Evolutionary Curriculum Training for DRL-Based Navigation Systems

Max Asselmeier, Zhaoyi Li, Kelin Yu +1

In recent years, Deep Reinforcement Learning (DRL) has emerged as a promising method for robot collision avoidance. However, such DRL models often come with limitations, such as ad…

cs.RO2023★ 9 cited

Language-Guided Traffic Simulation via Scene-Level Diffusion

Ziyuan Zhong, Davis Rempe, Yuxiao Chen +5

Realistic and controllable traffic simulation is a core capability that is necessary to accelerate autonomous vehicle (AV) development. However, current approaches for controlling…

cs.RO2023★ 1 cited

Zero-Shot Object Searching Using Large-scale Object Relationship Prior

Hongyi Chen, Ruinian Xu, Shuo Cheng +2

Home-assistant robots have been a long-standing research topic, and one of the biggest challenges is searching for required objects in housing environments. Previous object-goal na…

cs.RO2023★ 24 cited

MimicPlay: Long-Horizon Imitation Learning by Watching Human Play

Chen Wang, Linxi Fan, Jiankai Sun +5

Imitation learning from human demonstrations is a promising paradigm for teaching robots manipulation skills in the real world. However, learning complex long-horizon tasks often r…

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