Zobrazeno 1 - 10
of 57
pro vyhledávání: '"David Joseph Tan"'
We propose a novel convolutional operator for the task of point cloud completion. One striking characteristic of our approach is that, conversely to related work it does not require any max-pooling or voxelization operation. Instead, the proposed ope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2eca16841b79d90040e5553a71c10b53
http://arxiv.org/abs/2205.03899
http://arxiv.org/abs/2205.03899
Autor:
Ruofei Du, Alex Olwal, Mathieu Le Goc, Shengzhi Wu, Danhang Tang, Yinda Zhang, Jun Zhang, David Joseph Tan, Federico Tombari, David Kim
Publikováno v:
CHI Conference on Human Factors in Computing Systems Extended Abstracts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d40f1900e9969e1e2f118a5c7b670661
https://doi.org/10.1145/3491101.3519911
https://doi.org/10.1145/3491101.3519911
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585792
ECCV (3)
ECCV (3)
Point clouds are often the default choice for many applications as they exhibit more flexibility and efficiency than volumetric data. Nevertheless, their unorganized nature – points are stored in an unordered way – makes them less suited to be pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::372077f81092633b22e10fcfdec8ef56
https://doi.org/10.1007/978-3-030-58580-8_5
https://doi.org/10.1007/978-3-030-58580-8_5
Publikováno v:
3DV
Estimating the 3D shape of an object from a single or multiple images has gained popularity thanks to the recent breakthroughs powered by deep learning. Most approaches regress the full object shape in a canonical pose, possibly extrapolating the occ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43c7825f6dd30040ac235a84d0c61094
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-1
Deep learning approaches process data in a layer-by-layer way with intermediate (or latent) features. We aim at designing a general solution to optimize the latent manifolds to improve the performance on classification, segmentation, completion and/o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29e119ded137c4356a9da2170bd84232
https://doi.org/10.1109/tpami.2022.3160539
https://doi.org/10.1109/tpami.2022.3160539
Publikováno v:
International Journal of Computer Vision. 126:158-183
We demonstrate how 3D head tracking and pose estimation can be effectively and efficiently achieved from noisy RGB-D sequences. Our proposal leverages on a random forest framework, designed to regress the 3D head pose at every frame in a temporal tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd69f6d3f2ac3496fad1f4602e8e2c6f
https://doi.org/10.1007/s11263-017-0988-8
https://doi.org/10.1007/s11263-017-0988-8
Publikováno v:
ICCV
We propose a novel model for 3D semantic completion from a single depth image, based on a single encoder and three separate generators used to reconstruct different geometric and semantic representations of the original and completed scene, all shari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88bb7f213db7ab86c00fd2518b06d2c8
https://doi.org/10.1109/iccv.2019.00870
https://doi.org/10.1109/iccv.2019.00870
Autor:
Chiara Amat di San Filippo, Mohamed Alsheakhali, Federico Tombari, Vasileios Belagiannis, Nicola Rieke, Nassir Navab, David Joseph Tan, Abouzar Eslami
Publikováno v:
Medical Image Analysis. 34:82-100
Real-time visual tracking of a surgical instrument holds great potential for improving the outcome of retinal microsurgery by enabling new possibilities for computer-aided techniques such as augmented reality and automatic assessment of instrument ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8eb1831b73f728f6808fd0682027479b
https://doi.org/10.1016/j.media.2016.05.003
https://doi.org/10.1016/j.media.2016.05.003
Publikováno v:
3DV
We propose a method to reconstruct, complete and semantically label a 3D scene from a single input depth image. We improve the accuracy of the regressed semantic 3D maps by a novel architecture based on adversarial learning. In particular, we suggest
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::adb56c4b879b2c4b2bcd0f88686eebfc
https://doi.org/10.1109/3dv.2018.00056
https://doi.org/10.1109/3dv.2018.00056
Publikováno v:
Computer Vision – ECCV 2018 ISBN: 9783030012632
ECCV (14)
ECCV (14)
Effectively measuring the similarity between two human motions is necessary for several computer vision tasks such as gait analysis, person identification and action retrieval. Nevertheless, we believe that traditional approaches such as L2 distance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb8ca919bf9d72b3d5e64713b67762f7
https://doi.org/10.1007/978-3-030-01264-9_41
https://doi.org/10.1007/978-3-030-01264-9_41