15 citations · 43 across the 9 of their papers we have counts for
16 papers · 1 filter
A Critical Look at the Current Usage of Foundation Model for Dense Recognition Task
Shiqi Yang, Atsushi Hashimoto, Yoshitaka Ushiku
In recent years large model trained on huge amount of cross-modality data, which is usually be termed as foundation model, achieves conspicuous accomplishment in many fields, such…
Noisy Universal Domain Adaptation via Divergence Optimization for Visual Recognition
Qing Yu, Atsushi Hashimoto, Yoshitaka Ushiku
To transfer the knowledge learned from a labeled source domain to an unlabeled target domain, many studies have worked on universal domain adaptation (UniDA), where there is no con…
Divergence Optimization for Noisy Universal Domain Adaptation
Qing Yu, Atsushi Hashimoto, Yoshitaka Ushiku
Universal domain adaptation (UniDA) has been proposed to transfer knowledge learned from a label-rich source domain to a label-scarce target domain without any constraints on the l…
Crowd Density Forecasting by Modeling Patch-based Dynamics
Hiroaki Minoura, Ryo Yonetani, Mai Nishimura +1
Forecasting human activities observed in videos is a long-standing challenge in computer vision, which leads to various real-world applications such as mobile robots, autonomous dr…
Pose Graph Optimization for Unsupervised Monocular Visual Odometry
Yang Li, Yoshitaka Ushiku, Tatsuya Harada
Unsupervised Learning based monocular visual odometry (VO) has lately drawn significant attention for its potential in label-free leaning ability and robustness to camera parameter…
Multichannel Semantic Segmentation with Unsupervised Domain Adaptation
Kohei Watanabe, Kuniaki Saito, Yoshitaka Ushiku +1
Most contemporary robots have depth sensors, and research on semantic segmentation with RGBD images has shown that depth images boost the accuracy of segmentation. Since it is time…