Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Philipp Krähenbühl"'
Autor:
Jang Hyun Cho, Philipp Krähenbühl
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200731
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe87055ca2081b215564531aca27769b
https://doi.org/10.1007/978-3-031-20074-8_40
https://doi.org/10.1007/978-3-031-20074-8_40
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200762
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6be3e72e074328b0ad94860a5b52c818
https://doi.org/10.1007/978-3-031-20077-9_21
https://doi.org/10.1007/978-3-031-20077-9_21
Autor:
Yue Zhao, Philipp Krähenbühl
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198298
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24a98d1515c62132b23f6c2bf493e122
https://doi.org/10.1007/978-3-031-19830-4_28
https://doi.org/10.1007/978-3-031-19830-4_28
Autor:
Philipp Krähenbühl, Chao-Yuan Wu
Publikováno v:
CVPR
Our world offers a never-ending stream of visual stimuli, yet today's vision systems only accurately recognize patterns within a few seconds. These systems understand the present, but fail to contextualize it in past or future events. In this paper,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d65ec68fab9eea64253c2c3c5ee7e04
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585471
ECCV (4)
ECCV (4)
Tracking has traditionally been the art of following interest points through space and time. This changed with the rise of powerful deep networks. Nowadays, tracking is dominated by pipelines that perform object detection followed by temporal associa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::404ce357dfa23a2ae4f4f14c6fb9dc7d
https://doi.org/10.1007/978-3-030-58548-8_28
https://doi.org/10.1007/978-3-030-58548-8_28
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585730
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e273c05500aedfc066bdba536bae652
https://doi.org/10.1007/978-3-030-58574-7_40
https://doi.org/10.1007/978-3-030-58574-7_40
Publikováno v:
CVPR
Three-dimensional objects are commonly represented as 3D boxes in a point-cloud. This representation mimics the well-studied image-based 2D bounding-box detection but comes with additional challenges. Objects in a 3D world do not follow any particula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fe5e54438a79916932c29258b2f895c
Publikováno v:
CVPR
Training competitive deep video models is an order of magnitude slower than training their counterpart image models. Slow training causes long research cycles, which hinders progress in video understanding research. Following standard practice for tr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::759066eded09353e7e0cf48114a4dac7
http://arxiv.org/abs/1912.00998
http://arxiv.org/abs/1912.00998
Autor:
Alexei A. Efros, Kate Rakelly, Crystal Lee, Shiry Ginosar, Sarah Sachs, Brian Yin, Philipp Krähenbühl
Publikováno v:
IEEE Transactions on Computational Imaging. 3:421-431
Imagery offers a rich description of our world and communicates a volume and type of information that cannot be captured by text alone. Since the invention of the camera, an ever-increasing number of photographs document our "visual culture" compleme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72a6443ecc7f784c297395f689c2e9b1
https://doi.org/10.1109/tci.2017.2699865
https://doi.org/10.1109/tci.2017.2699865
Publikováno v:
Science robotics. 4(30)
Computer vision produces representations of scene content. Much computer vision research is predicated on the assumption that these intermediate representations are useful for action. Recent work at the intersection of machine learning and robotics c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73e035edfeb8df68f0ebdeb331e0a9c3
https://pubmed.ncbi.nlm.nih.gov/33137779
https://pubmed.ncbi.nlm.nih.gov/33137779