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of 6
pro vyhledávání: '"Hedlin, Eric"'
Autor:
Zhang, Congyi, Yang, Jinfan, Hedlin, Eric, Takikawa, Suzuran, Vining, Nicholas, Yi, Kwang Moo, Wang, Wenping, Sheffer, Alla
Compressed representations of 3D shapes that are compact, accurate, and can be processed efficiently directly in compressed form, are extremely useful for digital media applications. Recent approaches in this space focus on learned implicit or parame
Externí odkaz:
http://arxiv.org/abs/2409.06030
Autor:
Hedlin, Eric, Sharma, Gopal, Mahajan, Shweta, He, Xingzhe, Isack, Hossam, Rhodin, Abhishek Kar Helge, Tagliasacchi, Andrea, Yi, Kwang Moo
Unsupervised learning of keypoints and landmarks has seen significant progress with the help of modern neural network architectures, but performance is yet to match the supervised counterpart, making their practicability questionable. We leverage the
Externí odkaz:
http://arxiv.org/abs/2312.00065
Autor:
Hedlin, Eric, Sharma, Gopal, Mahajan, Shweta, Isack, Hossam, Kar, Abhishek, Tagliasacchi, Andrea, Yi, Kwang Moo
Text-to-image diffusion models are now capable of generating images that are often indistinguishable from real images. To generate such images, these models must understand the semantics of the objects they are asked to generate. In this work we show
Externí odkaz:
http://arxiv.org/abs/2305.15581
We introduce CN-DHF (Compact Neural Double-Height-Field), a novel hybrid neural implicit 3D shape representation that is dramatically more compact than the current state of the art. Our representation leverages Double-Height-Field (DHF) geometries, d
Externí odkaz:
http://arxiv.org/abs/2304.13141
Many human pose estimation methods estimate Skinned Multi-Person Linear (SMPL) models and regress the human joints from these SMPL estimates. In this work, we show that the most widely used SMPL-to-joint linear layer (joint regressor) is inaccurate,
Externí odkaz:
http://arxiv.org/abs/2205.00076
Autor:
Hedlin, Eric
In this thesis, we develop Computer Vision methods for Human body pose and stride length estimation. We first describe a framework for estimating the stride length of a walking subject from video using a multi-view camera setup. We specifically look
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f09a13ffefd0a801af5b6f1c792401a3