Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Yannis Kalantidis"'
Publikováno v:
Image Analysis ISBN: 9783031314346
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3cb58a18d206112c95463bb6c4725e52
https://doi.org/10.1007/978-3-031-31435-3_15
https://doi.org/10.1007/978-3-031-31435-3_15
Autor:
Fabien Baradel, Romain Bregier, Thibault Groueix, Philippe Weinzaepfel, Yannis Kalantidis, Gregory Rogez
Training state-of-the-art models for human pose estimation in videos requires datasets with annotations that are really hard and expensive to obtain. Although transformers have been recently utilized for body pose sequence modeling, related methods r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35b349aed332e80cbff64a202d5605ca
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197802
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cab6ea6ea09c05fae2362b7fb6a08faf
https://doi.org/10.1007/978-3-031-19781-9_23
https://doi.org/10.1007/978-3-031-19781-9_23
Autor:
Fabien Baradel, Thibault Groueix, Philippe Weinzaepfel, Romain Bregier, Yannis Kalantidis, Gregory Rogez
Training state-of-the-art models for human body pose and shape recovery from images or videos requires datasets with corresponding annotations that are really hard and expensive to obtain. Our goal in this paper is to study whether poses from 3D Moti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b9694258d238fdc32c5eaf7b234c8fa
http://arxiv.org/abs/2110.09243
http://arxiv.org/abs/2110.09243
Autor:
Yannis Kalantidis
Στην παρούσα εργασία προτείνονται βελτιώσεις στην οπτική αναζήτηση εικόνων, με τεχνικές που βασίζονται κυρίως σε ομαδοποίηση. Η ομαδοπ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60ac68fe1a7b848f29dc88c3b0cb9acf
https://doi.org/10.12681/eadd/38870
https://doi.org/10.12681/eadd/38870
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 41:1893-1908
Recent insights on language and vision with neural networks have been successfully applied to simple single-image visual question answering. However, to tackle real-life question answering problems on multimedia collections such as personal photo alb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ec1a5a63d7bfd166e604ac66d5e34d7
https://doi.org/10.1109/tpami.2018.2890628
https://doi.org/10.1109/tpami.2018.2890628
Publikováno v:
CVPR
Cross-modal retrieval methods build a common representation space for samples from multiple modalities, typically from the vision and the language domains. For images and their captions, the multiplicity of the correspondences makes the task particul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f353bcc9710fd227b28caa558898be34
http://arxiv.org/abs/2101.05068
http://arxiv.org/abs/2101.05068
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585228
ECCV (18)
ECCV (18)
When automatically generating a sentence description for an image or video, it often remains unclear how well the generated caption is grounded, that is whether the model uses the correct image regions to output particular words, or if the model is h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7820c1fc448b461ca5cd25c2fc155e32
https://doi.org/10.1007/978-3-030-58523-5_21
https://doi.org/10.1007/978-3-030-58523-5_21
Autor:
Marcus Rohrbach, Yannis Kalantidis, Laura Sevilla-Lara, Xudong Lin, Zheng Shou, Zhicheng Yan, Shih-Fu Chang
Publikováno v:
CVPR
Shou, Z, Lin, X, Kalantidis, Y, Sevilla-Lara, L, Rohrbach, M, Chang, S-F & Yan, Z 2020, DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition . in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition . Institute of Electrical and Electronics Engineers (IEEE), pp. 1268-1277, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, California, United States, 16/06/19 . https://doi.org/10.1109/CVPR.2019.00136
Shou, Z, Lin, X, Kalantidis, Y, Sevilla-Lara, L, Rohrbach, M, Chang, S-F & Yan, Z 2020, DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition . in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition . Institute of Electrical and Electronics Engineers (IEEE), pp. 1268-1277, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, California, United States, 16/06/19 . https://doi.org/10.1109/CVPR.2019.00136
Motion has shown to be useful for video understanding, where motion is typically represented by optical flow. However, computing flow from video frames is very time-consuming. Recent works directly leverage the motion vectors and residuals readily av
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::826970931022d289d40f2f481967defa
https://doi.org/10.1109/cvpr.2019.00136
https://doi.org/10.1109/cvpr.2019.00136
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Autor:
Zhicheng Yan, Haoqi Fan, Yannis Kalantidis, Yunpeng Chen, Yan Shuicheng, Jiashi Feng, Marcus Rohrbach, Bing Xu
Publikováno v:
ICCV
In natural images, information is conveyed at different frequencies where higher frequencies are usually encoded with fine details and lower frequencies are usually encoded with global structures. Similarly, the output feature maps of a convolution l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c04de604ffddacf880f37fdedbd2576b
http://arxiv.org/abs/1904.05049
http://arxiv.org/abs/1904.05049