Book
InstantGeoAvatar: Effective Geometry and Appearance Modeling of Animatable Avatars from Monocular Video
| Τίτλος: | InstantGeoAvatar: Effective Geometry and Appearance Modeling of Animatable Avatars from Monocular Video |
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| Συγγραφείς: | Alvaro Budria, Adrian Lopez-Rodriguez, Òscar Lorente, Francesc Moreno-Noguer |
| Συνεισφορές: | Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Ministerio de Ciencia e Innovación (España), European Commission, Moreno-Noguer, Francesc [0000-0002-8640-684X], Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72] |
| Πηγή: | Lecture Notes in Computer Science ISBN: 9789819609598 UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Digital.CSIC. Repositorio Institucional del CSIC Consejo Superior de Investigaciones Científicas (CSIC) |
| Publication Status: | Preprint |
| Στοιχεία εκδότη: | Springer Nature Singapore, 2024. |
| Έτος έκδοσης: | 2024 |
| Θεματικοί όροι: | FOS: Computer and information sciences, Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Interacció home-màquina, Computer Vision and Pattern Recognition (cs.CV), Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Computer Science - Computer Vision and Pattern Recognition, Graphics (cs.GR), 3D Computer Vision, Clothed Human Modeling, Human avatars, Computer Science - Graphics, Neural radiance fields, Human Avatars, Clothed human modeling, 3D computer vision, Neural Radiance Fields |
| Περιγραφή: | We present InstantGeoAvatar, a method for efficient and effective learning from monocular video of detailed 3D geometry and appearance of animatable implicit human avatars. Our key observation is that the optimization of a hash grid encoding to represent a signed distance function (SDF) of the human subject is fraught with instabilities and bad local minima. We thus propose a principled geometry-aware SDF regularization scheme that seamlessly fits into the volume rendering pipeline and adds negligible computational overhead. Our regularization scheme significantly outperforms previous approaches for training SDFs on hash grids. We obtain competitive results in geometry reconstruction and novel view synthesis in as little as five minutes of training time, a significant reduction from the several hours required by previous work. InstantGeoAvatar represents a significant leap forward towards achieving interactive reconstruction of virtual avatars. Accepted as poster to Asian Conference on Computer Vison (ACCV 2024) |
| Τύπος εγγράφου: | Part of book or chapter of book Article Conference object |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| DOI: | 10.1007/978-981-96-0960-4_16 |
| DOI: | 10.48550/arxiv.2411.01512 |
| DOI: | 10.13039/501100000780 |
| DOI: | 10.13039/501100004837 |
| DOI: | 10.13039/501100011033 |
| Σύνδεσμος πρόσβασης: | http://arxiv.org/abs/2411.01512 http://hdl.handle.net/10261/387911 https://api.elsevier.com/content/abstract/scopus_id/85212964933 https://hdl.handle.net/2117/433373 https://doi.org/10.1007/978-981-96-0960-4_16 |
| Rights: | Springer Nature TDM arXiv Non-Exclusive Distribution |
| Αριθμός Καταχώρησης: | edsair.doi.dedup.....be56df04015edfefbaa67ecd8b3d94fb |
| Βάση Δεδομένων: | OpenAIRE |
| DOI: | 10.1007/978-981-96-0960-4_16 |
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