30 citations · 193 across the 34 of their papers we have counts for
14 papers · 1 filter
TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain Adaptation
Toshihiko Matsuura, Kuniaki Saito, Tatsuya Harada
The task of unsupervised domain adaptation is proposed to transfer the knowledge of a label-rich domain (source domain) to a label-scarce domain (target domain). Matching feature d…
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…
Conditional Video Generation Using Action-Appearance Captions
Shohei Yamamoto, Antonio Tejero-de-Pablos, Yoshitaka Ushiku +1
The field of automatic video generation has received a boost thanks to the recent Generative Adversarial Networks (GANs). However, most existing methods cannot control the contents…
Strong-Weak Distribution Alignment for Adaptive Object Detection
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada +1
We propose an approach for unsupervised adaptation of object detectors from label-rich to label-poor domains which can significantly reduce annotation costs associated with detecti…
Learning to Explain with Complemental Examples
Atsushi Kanehira, Tatsuya Harada
This paper addresses the generation of explanations with visual examples. Given an input sample, we build a system that not only classifies it to a specific category, but also outp…
Multimodal Explanations by Predicting Counterfactuality in Videos
Atsushi Kanehira, Kentaro Takemoto, Sho Inayoshi +1
This study addresses generating counterfactual explanations with multimodal information. Our goal is not only to classify a video into a specific category, but also to provide expl…