30 citations · 193 across the 34 of their papers we have counts for
43 papers · 1 filter
Learning by Asking Questions for Knowledge-based Novel Object Recognition
Kohei Uehara, Tatsuya Harada
In real-world object recognition, there are numerous object classes to be recognized. Conventional image recognition based on supervised learning can only recognize object classes…
Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
Ziteng Cui, Guo-Jun Qi, Lin Gu +3
Dark environment becomes a challenge for computer vision algorithms owing to insufficient photons and undesirable noise. To enhance object detection in a dark environment, we propo…
Unsupervised Pose-Aware Part Decomposition for 3D Articulated Objects
Yuki Kawana, Yusuke Mukuta, Tatsuya Harada
Articulated objects exist widely in the real world. However, previous 3D generative methods for unsupervised part decomposition are unsuitable for such objects, because they assume…
Video Moment Retrieval with Text Query Considering Many-to-Many Correspondence Using Potentially Relevant Pair
Sho Maeoki, Yusuke Mukuta, Tatsuya Harada
In this paper we undertake the task of text-based video moment retrieval from a corpus of videos. To train the model, text-moment paired datasets were used to learn the correct cor…
Efficient training for future video generation based on hierarchical disentangled representation of latent variables
Naoya Fushishita, Antonio Tejero-de-Pablos, Yusuke Mukuta +1
Generating videos predicting the future of a given sequence has been an area of active research in recent years. However, an essential problem remains unsolved: most of the methods…
Neural Articulated Radiance Field
Atsuhiro Noguchi, Xiao Sun, Stephen Lin +1
We present Neural Articulated Radiance Field (NARF), a novel deformable 3D representation for articulated objects learned from images. While recent advances in 3D implicit represen…