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Autor:
Borges, Beatriz, Foroutan, Negar, Bayazit, Deniz, Sotnikova, Anna, Montariol, Syrielle, Nazaretzky, Tanya, Banaei, Mohammadreza, Sakhaeirad, Alireza, Servant, Philippe, Neshaei, Seyed Parsa, Frej, Jibril, Romanou, Angelika, Weiss, Gail, Mamooler, Sepideh, Chen, Zeming, Fan, Simin, Gao, Silin, Ismayilzada, Mete, Paul, Debjit, Schöpfer, Alexandre, Janchevski, Andrej, Tiede, Anja, Linden, Clarence, Troiani, Emanuele, Salvi, Francesco, Behrens, Freya, Orsi, Giacomo, Piccioli, Giovanni, Sevel, Hadrien, Coulon, Louis, Pineros-Rodriguez, Manuela, Bonnassies, Marin, Hellich, Pierre, van Gerwen, Puck, Gambhir, Sankalp, Pirelli, Solal, Blanchard, Thomas, Callens, Timothée, Aoun, Toni Abi, Alonso, Yannick Calvino, Cho, Yuri, Chiappa, Alberto, Sclocchi, Antonio, Bruno, Étienne, Hofhammer, Florian, Pescia, Gabriel, Rizk, Geovani, Dadi, Leello, Stoffl, Lucas, Ribeiro, Manoel Horta, Bovel, Matthieu, Pan, Yueyang, Radenovic, Aleksandra, Alahi, Alexandre, Mathis, Alexander, Bitbol, Anne-Florence, Faltings, Boi, Hébert, Cécile, Tuia, Devis, Maréchal, François, Candea, George, Carleo, Giuseppe, Chappelier, Jean-Cédric, Flammarion, Nicolas, Fürbringer, Jean-Marie, Pellet, Jean-Philippe, Aberer, Karl, Zdeborová, Lenka, Salathé, Marcel, Jaggi, Martin, Rajman, Martin, Payer, Mathias, Wyart, Matthieu, Gastpar, Michael, Ceriotti, Michele, Svensson, Ola, Lévêque, Olivier, Ienne, Paolo, Guerraoui, Rachid, West, Robert, Kashyap, Sanidhya, Piazza, Valerio, Simanis, Viesturs, Kuncak, Viktor, Cevher, Volkan, Schwaller, Philippe, Friedli, Sacha, Jermann, Patrick, Kaser, Tanja, Bosselut, Antoine
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they also pose significant challenges for assessment and learning outcomes.
Externí odkaz:
http://arxiv.org/abs/2408.11841
Publikováno v:
ICCV Link: https://openaccess.thecvf.com/content/ICCV2023/papers/Zhou_Rethinking_Pose_Estimation_in_Crowds_Overcoming_the_Detection_Information_Bottleneck_ICCV_2023_paper.pdf
Frequent interactions between individuals are a fundamental challenge for pose estimation algorithms. Current pipelines either use an object detector together with a pose estimator (top-down approach), or localize all body parts first and then link t
Externí odkaz:
http://arxiv.org/abs/2306.07879
We propose an end-to-end trainable approach for multi-instance pose estimation, called POET (POse Estimation Transformer). Combining a convolutional neural network with a transformer encoder-decoder architecture, we formulate multiinstance pose estim
Externí odkaz:
http://arxiv.org/abs/2103.12115
Publikováno v:
In Neural Networks January 2020 121:122-131
