Nov 5, 2024 · This paper introduces self-supervised neural network models to tackle several fundamental problems in the field of 3D human body analysis and processing.
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Nov 5, 2024 · This paper introduces self-supervised neural network models to tackle several fundamental problems in the field of 3D human body analysis and processing.
Nov 9, 2024 · This paper introduces self-supervised neural network models to tackle several fundamental problems in the field of 3D human body analysis ...
7 days ago · Bibliographic details on Self Supervised Networks for Learning Latent Space Representations of Human Body Scans and Motions.
Nov 6, 2024 · The paper proposes a framework for learning latent space representations of human body scans and motions using self-supervised neural networks.
We present Basis Restricted Elastic Shape Analysis (BaRe-ESA), a novel Riemannian framework for human body scan representation, interpolation and extrapolation.
Self Supervised Networks for Learning Latent Space Representations of Human Body Scans and Motions. E Hartman, N Charon, M Bauer. arXiv preprint arXiv ...
We propose a novel self-supervised multi-task learning framework (SSMT), which integrates two key modules: a discriminative-based module and a generative-based ...
This paper introduces self-supervised neural network models to tackle several fundamental problems in the field of 3D human body analysis and processing. First, ...
We propose a continuous, 3D-structure aware neural scene representation, Scene Representa- tion Networks (SRNs). This enables the learning of priors over 3D ...