34 citations · 102 across the 29 of their papers we have counts for
6 papers · 1 filter
Rethinking Generic Camera Models for Deep Single Image Camera Calibration to Recover Rotation and Fisheye Distortion
Nobuhiko Wakai, Satoshi Sato, Yasunori Ishii +1
Although recent learning-based calibration methods can predict extrinsic and intrinsic camera parameters from a single image, the accuracy of these methods is degraded in fisheye i…
ST-ABN: Visual Explanation Taking into Account Spatio-temporal Information for Video Recognition
Masahiro Mitsuhara, Tsubasa Hirakawa, Takayoshi Yamashita +1
It is difficult for people to interpret the decision-making in the inference process of deep neural networks. Visual explanation is one method for interpreting the decision-making…
CutDepth:Edge-aware Data Augmentation in Depth Estimation
Yasunori Ishii, Takayoshi Yamashita
It is difficult to collect data on a large scale in a monocular depth estimation because the task requires the simultaneous acquisition of RGB images and depths. Data augmentation…
Deep Ensemble Collaborative Learning by using Knowledge-transfer Graph for Fine-grained Object Classification
Naoki Okamoto, Soma Minami, Tsubasa Hirakawa +2
Mutual learning, in which multiple networks learn by sharing their knowledge, improves the performance of each network. However, the performance of ensembles of networks that have…
Visual Explanation using Attention Mechanism in Actor-Critic-based Deep Reinforcement Learning
Hidenori Itaya, Tsubasa Hirakawa, Takayoshi Yamashita +2
Deep reinforcement learning (DRL) has great potential for acquiring the optimal action in complex environments such as games and robot control. However, it is difficult to analyze…
Predicting and Attending to Damaging Collisions for Placing Everyday Objects in Photo-Realistic Simulations
Aly Magassouba, Komei Sugiura, Angelica Nakayama +4
Placing objects is a fundamental task for domestic service robots (DSRs). Thus, inferring the collision-risk before a placing motion is crucial for achieving the requested task. Th…