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Piotr Dollár

Facebook AI Research

33 papers hereh-index 54214.5k citations72 works total

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

author position
  • first author2
  • middle author19
  • last author12

Across the 33 of 33 papers where every author was matched, so the position is known.

fields
  • cs.CV31
  • stat.ML2
affiliations
  • Facebook AI Research
Homepage
same name
  • Piotr Dollár — 4 papers, h 6

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
20142023
most citedAccurate, Large Minibatch SGD: Training ImageNet in 1 Hour

2.5k citations · 9.9k across the 27 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

LVIS: A Dataset for Large Vocabulary Instance Segmentation

Agrim Gupta, Piotr Dollár, Ross Girshick

Progress on object detection is enabled by datasets that focus the research community's attention on open challenges. This process led us from simple images to complex scenes and f…

cs.CV2019

On Network Design Spaces for Visual Recognition

Ilija Radosavovic, Justin Johnson, Saining Xie +2

Over the past several years progress in designing better neural network architectures for visual recognition has been substantial. To help sustain this rate of progress, in this wo…

cs.CV2019★ 36 cited

TensorMask: A Foundation for Dense Object Segmentation

Xinlei Chen, Ross Girshick, Kaiming He +1

Sliding-window object detectors that generate bounding-box object predictions over a dense, regular grid have advanced rapidly and proven popular. In contrast, modern instance segm…

cs.CV2019★ 61 cited

Panoptic Feature Pyramid Networks

Alexander Kirillov, Ross Girshick, Kaiming He +1

The recently introduced panoptic segmentation task has renewed our community's interest in unifying the tasks of instance segmentation (for thing classes) and semantic segmentation…

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