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Face Deduplication Collection

TELUS Digital · United Kingdom

원격영어

직무 소개

기업 공고 원문에서 · TELUS Digital · 2026년 9월 12일 게시

The objective of this project is to collect a large and diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training at TELUS.

The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. The collection includes:

  • Current Neutral Selfies – clean frontal selfies serving as high-quality identity references, with natural variation in appearance and surroundings.
  • Current Head-Pose Captures – selfies captured in assigned head directions to introduce pose variation.
  • Historical Images – older photos from participants’ galleries to capture natural aging and long-term appearance changes.

The objective of this project is to collect a large and diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training at TELUS.

To qualify for payment, you must submit a minimum of 20 valid images. The maximum payout is based on 24 accepted images. Due to the strict automated and manual Quality Control (QC) process, we strongly recommend submitting 30 images to help ensure that enough images remain valid after review

Note: Please use a Gmail address as your primary account when applying for this project.

Qualification path

No specific education is needed to perform the project task.

언급된 기술

quality

모든 공고에서 나의 매치 점수를 확인하세요

BabZituna는 모든 공고를 내 프로필과 비교해 여섯 가지 실제 기준으로 점수를 매기고, 왜 그 점수가 나왔는지 보여 줍니다. 공정성 감사도 거쳤습니다(공개 편향 감사 읽기).

앱 받기 → ✓ 구직자는 100% 무료
한 공고의 점수 산출 예시
기술96경력90근무지84근무 방식74고용 형태61급여데이터 없음

예시 수치이며 실제 지원자가 아닙니다. 각 기준은 내 프로필을 바탕으로 100점 만점으로 채점하며, 측정할 수 없는 기준은 추측하지 않고 그렇다고 표시합니다.