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Found 5 papers, 1 papers with code
One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation
Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability.
Dense Keypoints via Multiview Supervision
(2) Geometric consistency: every point in the continuous correspondence fields must satisfy the multiview consistency collectively.
HUMBI: A Large Multiview Dataset of Human Body Expressions and Benchmark Challenge
We demonstrate that HUMBI is highly effective in learning and reconstructing a complete human model and is complementary to the existing datasets of human body expressions with limited views and subjects such as MPII-Gaze, Multi-PIE, Human3. 6M, and Panoptic Studio datasets.
Semi-supervised Dense Keypoints Using Unlabeled Multiview Images
(2) Geometric consistency: every point in the continuous correspondence fields must satisfy the multiview consistency collectively.
HUMBI: A Large Multiview Dataset of Human Body Expressions
This paper presents a new large multiview dataset called HUMBI for human body expressions with natural clothing.
