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Joseph Campbell

28 papers hereh-index 11685 citations33 works total

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

author position
  • first author3
  • middle author22
  • last author3

Across the 28 of 28 papers where every author was matched, so the position is known.

fields
  • cs.LG9
  • cs.RO8
  • cs.AI4
  • cs.CV4
  • cs.CL2
  • cs.MA1
same name
  • Joseph Campbell — 5 papers, h 7
  • Joseph Campbell — 4 papers, h 2
  • Joseph Campbell — 3 papers, h 1
  • Joseph Campbell — 1 paper
  • Joseph Campbell — 1 paper
  • Joseph Campbell — 1 paper, h 3

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
20162026
most citedTheory of Mind for Multi-Agent Collaboration via Large Language Models

73 citations · 115 across the 28 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Symbolic Graph Inference for Compound Scene Understanding

FNU Aryan, Simon Stepputtis, Sarthak Bhagat +4

Scene understanding is a fundamental capability needed in many domains, ranging from question-answering to robotics. Unlike recent end-to-end approaches that must explicitly learn…

cs.CV2024★ 1 cited

HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation

Ce Zhang, Simon Stepputtis, Joseph Campbell +2

Being able to understand visual scenes is a precursor for many downstream tasks, including autonomous driving, robotics, and other vision-based approaches. A common approach enabli…

cs.CV2023★ 1 cited

Knowledge-Guided Short-Context Action Anticipation in Human-Centric Videos

Sarthak Bhagat, Simon Stepputtis, Joseph Campbell +1

This work focuses on anticipating long-term human actions, particularly using short video segments, which can speed up editing workflows through improved suggestions while fosterin…

cs.CV2023★ 1 cited

Sample-Efficient Learning of Novel Visual Concepts

Sarthak Bhagat, Simon Stepputtis, Joseph Campbell +1

Despite the advances made in visual object recognition, state-of-the-art deep learning models struggle to effectively recognize novel objects in a few-shot setting where only a lim…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.