人脸去重收集
Face Deduplication Collection
本项目的目标是收集大量且多样化的当前中性自拍、头部姿态捕捉图像以及历史面部图像，以支持TELUSS的机器学习研究和面部识别模型训练。
任务
重点在于捕捉光照、姿势、表情、配饰、环境和年龄变化等现实世界中的差异，以提高模型的准确性与鲁棒性。收集的内容包括：
要求
- 当前中性自拍 – 清晰的正面自拍，作为高质量的身份参考，具有自然的外貌和环境变化。
- 当前头部姿态捕捉 – 在指定头部方向下拍摄的自拍，以引入姿态变化。
- 历史图像 – 参与者相册中的旧照片，用于捕捉自然的衰老和长期外貌变化。
**无需特定教育背景即可完成该项目任务。**
要获得报酬，您必须提交至少20张有效的图像。最高报酬基于24张被接受的图像。由于严格的自动化和人工质量控制（QC）流程，我们强烈建议提交30张图像，以确保在审核后仍有足够多的有效图像。
参与本项目的总收益为13.20美元。
最初发布于喜马拉雅山
查看英文原文
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.
Tasks
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:
Requirements
- 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.
**No specific education is needed to perform the project task.**
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
Total earnings while participating in this project would be$13.20 USD.
Originally posted on Himalayas