“Generating 3D Human Texture From a Single Image With Sampling and Refinement” by Cha, Seo, Ashtari and Noh

  • ©Sihun Cha, Kwanggyoon Seo, Amirsaman Ashtari, and Junyong Noh

Conference:


Type(s):


Entry Number: 50

Title:

    Generating 3D Human Texture From a Single Image With Sampling and Refinement

Presenter(s)/Author(s):



Abstract:


    Generating the texture map for a 3D human mesh from a single image is challenging. To generate a plausible texture map, the invisible parts of the texture need to be synthesized with relevance to the visible part and the texture should semantically align to the UV space of the template mesh. To overcome such challenges, we propose a novel method that incorporates SamplerNet and RefineNet. SamplerNet predicts a sampling grid that enables sampling from the given visible texture information, and RefineNet refines the sampled texture to maintain spatial alignment.

References:


    Thiemo Alldieck, Marcus Magnor, Bharat Lal Bhatnagar, Christian Theobalt, and Gerard Pons-Moll. 2019. Learning to reconstruct people in clothing from a single RGB camera. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 1175–1186.Google ScholarCross Ref
    Rıza Alp Güler, Natalia Neverova, and Iasonas Kokkinos. 2018. Densepose: Dense human pose estimation in the wild. In Proceedings of the IEEE conference on computer vision and pattern recognition. 7297–7306.Google ScholarCross Ref
    Angjoo Kanazawa, Michael J Black, David W Jacobs, and Jitendra Malik. 2018. End-to-end recovery of human shape and pose. In Proceedings of the IEEE conference on computer vision and pattern recognition. 7122–7131.Google ScholarCross Ref
    Verica Lazova, Eldar Insafutdinov, and Gerard Pons-Moll. 2019. 360-degree textures of people in clothing from a single image. In 2019 International Conference on 3D Vision (3DV). IEEE, 643–653.Google ScholarCross Ref
    Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J Black. 2015. SMPL: A skinned multi-person linear model. ACM transactions on graphics (TOG) 34, 6 (2015), 1–16.Google Scholar
    Jian Wang, Yunshan Zhong, Yachun Li, Chi Zhang, and Yichen Wei. 2019. Re-identification supervised texture generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 11846–11856.Google ScholarCross Ref
    Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang. 2018. The unreasonable effectiveness of deep features as a perceptual metric. In Proceedings of the IEEE conference on computer vision and pattern recognition. 586–595.Google ScholarCross Ref


ACM Digital Library Publication:



Overview Page: