The Multi-PIE (Multi Pose, Illumination, Expressions) dataset consists of face images of 337 subjects taken under different pose, illumination and expressions. The pose range contains 15 discrete views, capturing a face profile-to-profile. Illumination changes were modeled using 19 flashlights located in different places of the room.

Description

This dataset contains raw scores in plain text format of several biometric (face and speaker) recognition systems applied on several datasets such as BANCA, Arface, FRGC, GBU, LFW, Multi-PIE, MOBIO, CAS-PEAL, NIST SRE 2012.

The biometric recognition systems are described in the aforementioned manuscript and encompasses Gaussian mixture models, inter-session variability modelling, joint factor analysis and probabilistic linear discriminant analysis.

The databases considered are the following ones:

• BANCA
• AR face database
• Face Recognition Grand Challenge version 2
• The Good, The Bad and the Ugly
• Labeled Faces in the Wild
• Multi-PIE
• MOBIO
• CAS-PEAL
• NIST Speaker Recognition Evaluation 2012

These scores allow to replicate easily and quickly the plots of the manuscript by using the following package:
http://pypi.python.org/pypi/xbob.thesis.elshafey2014

Citation

If you use this dataset in your publication, we would appreciate that you cite the following thesis:

Laurent El Shafey, “Scalable Probabilistic Models for Face and Speaker Recognition”, PhD thesis, 2014.
http://publications.idiap.ch/index.php/publications/show/2830

Information about City''s authorized spending limit, contract lifetime (called inception-to-date) ordering and spending. Contracts are visible only while active. For the purposes of the Online Contract Catalog Flat File, a contract is a long-term (multi-year) contract for goods and services, and contracts for Construction activity. Within the City, these are referred to as Master Agreements and Central Purchase Contracts.

What is PIE-Bench++?

PIE-Bench++ builds upon the foundation laid by the original PIE-Bench dataset introduced by (Ju et al., 2024), designed to provide a comprehensive benchmark for multi-aspect image editing evaluation. This enhanced dataset contains 700 images and prompts across nine distinct edit categories, encompassing a wide range of manipulations:

Object-Level Manipulations: Additions, removals, and modifications of objects within the image. Attribute-Level Manipulations:… See the full description on the dataset page: https://huggingface.co/datasets/UB-CVML-Group/PIE_Bench_pp.

Replication package for the article Bochet, Olivier, Manshu Khanna, Simon Siegenthaler (2023), Beyond Dividing the Pie: Multi-Issue Bargaining in the Laboratory. The Review of Economic Studies.

The replication package contains the data and software code to replicate the statistical analysis, tables, and figures published in the article and the online appendix. It only contains the experimental instructions.