Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Hachiuma, Ryo"'
A crowd density forecasting task aims to predict how the crowd density map will change in the future from observed past crowd density maps. However, the past crowd density maps are often incomplete due to the miss-detection of pedestrians, and it is
Externí odkaz:
http://arxiv.org/abs/2407.14725
Large language models (LLMs) have enhanced the capacity of vision-language models to caption visual text. This generative approach to image caption enrichment further makes textual captions more descriptive, improving alignment with the visual contex
Externí odkaz:
http://arxiv.org/abs/2406.13912
Predicting future human behavior from egocentric videos is a challenging but critical task for human intention understanding. Existing methods for forecasting 2D hand positions rely on visual representations and mainly focus on hand-object interactio
Externí odkaz:
http://arxiv.org/abs/2405.20030
We address a novel cross-domain few-shot learning task (CD-FSL) with multimodal input and unlabeled target data for egocentric action recognition. This paper simultaneously tackles two critical challenges associated with egocentric action recognition
Externí odkaz:
http://arxiv.org/abs/2405.19917
Surgical tool detection is essential for analyzing and evaluating minimally invasive surgery videos. Current approaches are mostly based on supervised methods that require large, fully instance-level labels (i.e., bounding boxes). However, large imag
Externí odkaz:
http://arxiv.org/abs/2401.02791
Autor:
Zia, Aneeq, Bhattacharyya, Kiran, Liu, Xi, Berniker, Max, Wang, Ziheng, Nespolo, Rogerio, Kondo, Satoshi, Kasai, Satoshi, Hirasawa, Kousuke, Liu, Bo, Austin, David, Wang, Yiheng, Futrega, Michal, Puget, Jean-Francois, Li, Zhenqiang, Sato, Yoichi, Fujii, Ryo, Hachiuma, Ryo, Masuda, Mana, Saito, Hideo, Wang, An, Xu, Mengya, Islam, Mobarakol, Bai, Long, Pang, Winnie, Ren, Hongliang, Nwoye, Chinedu, Sestini, Luca, Padoy, Nicolas, Nielsen, Maximilian, Schüttler, Samuel, Sentker, Thilo, Husseini, Hümeyra, Baltruschat, Ivo, Schmitz, Rüdiger, Werner, René, Matsun, Aleksandr, Farooq, Mugariya, Saaed, Numan, Viera, Jose Renato Restom, Yaqub, Mohammad, Getty, Neil, Xia, Fangfang, Zhao, Zixuan, Duan, Xiaotian, Yao, Xing, Lou, Ange, Yang, Hao, Han, Jintong, Noble, Jack, Wu, Jie Ying, Alshirbaji, Tamer Abdulbaki, Jalal, Nour Aldeen, Arabian, Herag, Ding, Ning, Moeller, Knut, Chen, Weiliang, He, Quan, Bilal, Muhammad, Akinosho, Taofeek, Qayyum, Adnan, Caputo, Massimo, Vohra, Hunaid, Loizou, Michael, Ajayi, Anuoluwapo, Berrou, Ilhem, Niyi-Odumosu, Faatihah, Maier-Hein, Lena, Stoyanov, Danail, Speidel, Stefanie, Jarc, Anthony
The ability to automatically detect and track surgical instruments in endoscopic videos can enable transformational interventions. Assessing surgical performance and efficiency, identifying skilled tool use and choreography, and planning operational
Externí odkaz:
http://arxiv.org/abs/2305.07152
In this paper, we present an end-to-end unsupervised anomaly detection framework for 3D point clouds. To the best of our knowledge, this is the first work to tackle the anomaly detection task on a general object represented by a 3D point cloud. We pr
Externí odkaz:
http://arxiv.org/abs/2304.03420
Recording surgery in operating rooms is an essential task for education and evaluation of medical treatment. However, recording the desired targets, such as the surgery field, surgical tools, or doctor's hands, is difficult because the targets are he
Externí odkaz:
http://arxiv.org/abs/2303.15947
This paper simultaneously addresses three limitations associated with conventional skeleton-based action recognition; skeleton detection and tracking errors, poor variety of the targeted actions, as well as person-wise and frame-wise action recogniti
Externí odkaz:
http://arxiv.org/abs/2303.15270
This study investigates unsupervised anomaly action recognition, which identifies video-level abnormal-human-behavior events in an unsupervised manner without abnormal samples, and simultaneously addresses three limitations in the conventional skelet
Externí odkaz:
http://arxiv.org/abs/2303.15167