Zobrazeno 1 - 10
of 916
pro vyhledávání: '"SATO, Yoichi"'
We present a contrastive learning framework based on in-the-wild hand images tailored for pre-training 3D hand pose estimators, dubbed HandCLR. Pre-training on large-scale images achieves promising results in various tasks, but prior 3D hand pose pre
Externí odkaz:
http://arxiv.org/abs/2409.09714
Autor:
Kong, Quan, Kawana, Yuki, Saini, Rajat, Kumar, Ashutosh, Pan, Jingjing, Gu, Ta, Ozao, Yohei, Opra, Balazs, Anastasiu, David C., Sato, Yoichi, Kobori, Norimasa
In this paper, we address the challenge of fine-grained video event understanding in traffic scenarios, vital for autonomous driving and safety. Traditional datasets focus on driver or vehicle behavior, often neglecting pedestrian perspectives. To fi
Externí odkaz:
http://arxiv.org/abs/2407.15350
Delving into the realm of egocentric vision, the advancement of referring video object segmentation (RVOS) stands as pivotal in understanding human activities. However, existing RVOS task primarily relies on static attributes such as object names to
Externí odkaz:
http://arxiv.org/abs/2407.07402
Compared with visual signals, Inertial Measurement Units (IMUs) placed on human limbs can capture accurate motion signals while being robust to lighting variation and occlusion. While these characteristics are intuitively valuable to help egocentric
Externí odkaz:
http://arxiv.org/abs/2407.06628
Temporally localizing the presence of object states in videos is crucial in understanding human activities beyond actions and objects. This task has suffered from a lack of training data due to object states' inherent ambiguity and variety. To avoid
Externí odkaz:
http://arxiv.org/abs/2405.01090
Autor:
Fan, Zicong, Ohkawa, Takehiko, Yang, Linlin, Lin, Nie, Zhou, Zhishan, Zhou, Shihao, Liang, Jiajun, Gao, Zhong, Zhang, Xuanyang, Zhang, Xue, Li, Fei, Liu, Zheng, Lu, Feng, Zeid, Karim Abou, Leibe, Bastian, On, Jeongwan, Baek, Seungryul, Prakash, Aditya, Gupta, Saurabh, He, Kun, Sato, Yoichi, Hilliges, Otmar, Chang, Hyung Jin, Yao, Angela
We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic 3Dunderstanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion generation.
Externí odkaz:
http://arxiv.org/abs/2403.16428
The pursuit of accurate 3D hand pose estimation stands as a keystone for understanding human activity in the realm of egocentric vision. The majority of existing estimation methods still rely on single-view images as input, leading to potential limit
Externí odkaz:
http://arxiv.org/abs/2403.04381
Autor:
Yagi, Takuma, Ohashi, Misaki, Huang, Yifei, Furuta, Ryosuke, Adachi, Shungo, Mitsuyama, Toutai, Sato, Yoichi
In the development of science, accurate and reproducible documentation of the experimental process is crucial. Automatic recognition of the actions in experiments from videos would help experimenters by complementing the recording of experiments. Tow
Externí odkaz:
http://arxiv.org/abs/2402.00293
Autor:
Grauman, Kristen, Westbury, Andrew, Torresani, Lorenzo, Kitani, Kris, Malik, Jitendra, Afouras, Triantafyllos, Ashutosh, Kumar, Baiyya, Vijay, Bansal, Siddhant, Boote, Bikram, Byrne, Eugene, Chavis, Zach, Chen, Joya, Cheng, Feng, Chu, Fu-Jen, Crane, Sean, Dasgupta, Avijit, Dong, Jing, Escobar, Maria, Forigua, Cristhian, Gebreselasie, Abrham, Haresh, Sanjay, Huang, Jing, Islam, Md Mohaiminul, Jain, Suyog, Khirodkar, Rawal, Kukreja, Devansh, Liang, Kevin J, Liu, Jia-Wei, Majumder, Sagnik, Mao, Yongsen, Martin, Miguel, Mavroudi, Effrosyni, Nagarajan, Tushar, Ragusa, Francesco, Ramakrishnan, Santhosh Kumar, Seminara, Luigi, Somayazulu, Arjun, Song, Yale, Su, Shan, Xue, Zihui, Zhang, Edward, Zhang, Jinxu, Castillo, Angela, Chen, Changan, Fu, Xinzhu, Furuta, Ryosuke, Gonzalez, Cristina, Gupta, Prince, Hu, Jiabo, Huang, Yifei, Huang, Yiming, Khoo, Weslie, Kumar, Anush, Kuo, Robert, Lakhavani, Sach, Liu, Miao, Luo, Mi, Luo, Zhengyi, Meredith, Brighid, Miller, Austin, Oguntola, Oluwatumininu, Pan, Xiaqing, Peng, Penny, Pramanick, Shraman, Ramazanova, Merey, Ryan, Fiona, Shan, Wei, Somasundaram, Kiran, Song, Chenan, Southerland, Audrey, Tateno, Masatoshi, Wang, Huiyu, Wang, Yuchen, Yagi, Takuma, Yan, Mingfei, Yang, Xitong, Yu, Zecheng, Zha, Shengxin Cindy, Zhao, Chen, Zhao, Ziwei, Zhu, Zhifan, Zhuo, Jeff, Arbelaez, Pablo, Bertasius, Gedas, Crandall, David, Damen, Dima, Engel, Jakob, Farinella, Giovanni Maria, Furnari, Antonino, Ghanem, Bernard, Hoffman, Judy, Jawahar, C. V., Newcombe, Richard, Park, Hyun Soo, Rehg, James M., Sato, Yoichi, Savva, Manolis, Shi, Jianbo, Shou, Mike Zheng, Wray, Michael
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric video of skilled human activities (e.g., sports, music, dance, bike re
Externí odkaz:
http://arxiv.org/abs/2311.18259
Autor:
Wen, Yilin, Pan, Hao, Ohkawa, Takehiko, Yang, Lei, Pan, Jia, Sato, Yoichi, Komura, Taku, Wang, Wenping
We present a novel unified framework that concurrently tackles recognition and future prediction for human hand pose and action modeling. Previous works generally provide isolated solutions for either recognition or prediction, which not only increas
Externí odkaz:
http://arxiv.org/abs/2311.17366