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Fernando De la Torre

4 papers here

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

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
ORCID 0000-0002-5143-3709
same name
  • Fernando De la Torre — 5 papers
  • Fernando de la Torre — 5 papers, h 5
  • Fernando De la Torre — 5 papers, h 4
  • Fernando De la Torre — 4 papers, h 2
  • Fernando De la Torre — 3 papers, h 5
  • Fernando de la Torre — 3 papers, 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
20142023
most citedSupervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision

44 citations · 62 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

Zero-shot Model Diagnosis

Jinqi Luo, Zhaoning Wang, Chen Henry Wu +2

When it comes to deploying deep vision models, the behavior of these systems must be explicable to ensure confidence in their reliability and fairness. A common approach to evaluat…

cs.CV2023★ 1 cited

Semantic Image Attack for Visual Model Diagnosis

Jinqi Luo, Zhaoning Wang, Chen Henry Wu +2

In practice, metric analysis on a specific train and test dataset does not guarantee reliable or fair ML models. This is partially due to the fact that obtaining a balanced, divers…

cs.CV2016★ 17 cited

Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection

Wen-Sheng Chu, Fernando De la Torre, Jeffrey F. Cohn

Facial action units (AUs) are essential to decode human facial expressions. Researchers have focused on training AU detectors with a variety of features and classifiers. However, s…

cs.CV2014★ 44 cited

Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision

Xuehan Xiong, Fernando De la Torre

Many computer vision problems (e.g., camera calibration, image alignment, structure from motion) are solved with nonlinear optimization methods. It is generally accepted that secon…

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