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Antonio M. López

22 papers hereh-index 399.7k citations137 works total

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

author position
  • first author1
  • middle author9
  • last author12

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV22
same name
  • Antonio M. López — 6 papers, h 2
  • Antonio M. López — 5 papers, h 4
  • Antonio M. López — 4 papers, h 1
  • Antonio M. López — 2 papers, h 5
  • Antonio M. López — 1 paper
  • Antonio M. López — 1 paper, h 1

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 citedEmbedded real-time stereo estimation via Semi-Global Matching on the GPU

168 citations · 316 across the 18 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019★ 17 cited

Active Learning for Deep Detection Neural Networks

Hamed H. Aghdam, Abel Gonzalez-Garcia, Joost van de Weijer +1

The cost of drawing object bounding boxes (i.e. labeling) for millions of images is prohibitively high. For instance, labeling pedestrians in a regular urban image could take 35 se…

cs.CV2019★ 8 cited

Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation

Zhijie Fang, Antonio M. López

Anticipating the intentions of vulnerable road users (VRUs) such as pedestrians and cyclists is critical for performing safe and comfortable driving maneuvers. This is the case for…

cs.CV2019★ 9 cited

Slanted Stixels: A way to represent steep streets

Daniel Hernandez-Juarez, Lukas Schneider, Pau Cebrian +6

This work presents and evaluates a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather re…

cs.CV2019

Temporal Coherence for Active Learning in Videos

Javad Zolfaghari Bengar, Abel Gonzalez-Garcia, Gabriel Villalonga +5

Autonomous driving systems require huge amounts of data to train. Manual annotation of this data is time-consuming and prohibitively expensive since it involves human resources. Th…

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