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David Held

Carnegie Mellon University

28 papers hereh-index 6322.3k citations196 works total

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

author position
  • first author1
  • middle author11
  • last author15

Across the 27 of 28 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • cs.RO9
  • cs.LG4
affiliations
  • Carnegie Mellon University
Homepage
same name
  • David Held — 9 papers, h 7
  • David Held — 9 papers, h 3
  • David Held — 8 papers, h 16
  • David Held — 6 papers
  • David Held — 4 papers, h 1
  • David Held — 3 papers, h 4

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
20172023
most citedConstrained Policy Optimization

112 citations · 318 across the 20 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

Deep Projective Rotation Estimation through Relative Supervision

Brian Okorn, Chuer Pan, Martial Hebert +1

Orientation estimation is the core to a variety of vision and robotics tasks such as camera and object pose estimation. Deep learning has offered a way to develop image-based orien…

cs.CV2022★ 1 cited

Differentiable Raycasting for Self-supervised Occupancy Forecasting

Tarasha Khurana, Peiyun Hu, Achal Dave +3

Motion planning for safe autonomous driving requires learning how the environment around an ego-vehicle evolves with time. Ego-centric perception of driveable regions in a scene no…

cs.LG2022★ 14 cited

DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools

Xingyu Lin, Zhiao Huang, Yunzhu Li +3

We consider the problem of sequential robotic manipulation of deformable objects using tools. Previous works have shown that differentiable physics simulators provide gradients to…

cs.RO2022

Self-supervised Transparent Liquid Segmentation for Robotic Pouring

Gautham Narayan Narasimhan, Kai Zhang, Ben Eisner +2

Liquid state estimation is important for robotics tasks such as pouring; however, estimating the state of transparent liquids is a challenging problem. We propose a novel segmentat…

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