VGGHeads：用於3D人頭的大規模合成數據集

VGGHeads: A Large-Scale Synthetic Dataset for 3D Human Heads

July 25, 2024

作者: Orest Kupyn, Eugene Khvedchenia, Christian Rupprecht

cs.AI

摘要

人頭檢測、關鍵點估計和3D頭部模型擬合是具有許多應用的重要任務。然而，傳統的現實世界數據集往往存在偏見、隱私和道德問題，並且它們是在實驗室環境中記錄的，這使得訓練模型難以泛化。在這裡，我們介紹VGGHeads - 一個使用擴散模型生成的大規模合成數據集，用於人頭檢測和3D網格估計。我們的數據集包含超過100萬張高分辨率圖像，每張圖像都標註了詳細的3D頭部網格、面部標誌和邊界框。使用這個數據集，我們介紹了一種新的模型架構，能夠在單張圖像中的單一步驟中同時檢測頭部和重建頭部網格。通過廣泛的實驗評估，我們證明了在我們的合成數據上訓練的模型在真實圖像上取得了強大的性能。此外，我們的數據集的多功能性使其適用於各種任務，提供了對人類頭部的一般和全面的表示。此外，我們提供了有關合成數據生成管道的詳細信息，使其可以被重新用於其他任務和領域。

English

Human head detection, keypoint estimation, and 3D head model fitting are important tasks with many applications. However, traditional real-world datasets often suffer from bias, privacy, and ethical concerns, and they have been recorded in laboratory environments, which makes it difficult for trained models to generalize. Here, we introduce VGGHeads -- a large scale synthetic dataset generated with diffusion models for human head detection and 3D mesh estimation. Our dataset comprises over 1 million high-resolution images, each annotated with detailed 3D head meshes, facial landmarks, and bounding boxes. Using this dataset we introduce a new model architecture capable of simultaneous heads detection and head meshes reconstruction from a single image in a single step. Through extensive experimental evaluations, we demonstrate that models trained on our synthetic data achieve strong performance on real images. Furthermore, the versatility of our dataset makes it applicable across a broad spectrum of tasks, offering a general and comprehensive representation of human heads. Additionally, we provide detailed information about the synthetic data generation pipeline, enabling it to be re-used for other tasks and domains.