18 citations · 30 across the 5 of their papers we have counts for
4 papers · 1 filter
Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score
He Huang, Shunta Saito, Yuta Kikuchi +3
Scene graph parsing aims to detect objects in an image scene and recognize their relations. Recent approaches have achieved high average scores on some popular benchmarks, but fail…
Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN
Masaki Saito, Shunta Saito, Masanori Koyama +1
Training of Generative Adversarial Network (GAN) on a video dataset is a challenge because of the sheer size of the dataset and the complexity of each observation. In general, the…
ChainerCV: a Library for Deep Learning in Computer Vision
Yusuke Niitani, Toru Ogawa, Shunta Saito +1
Despite significant progress of deep learning in the field of computer vision, there has not been a software library that covers these methods in a unifying manner. We introduce Ch…
Distantly Supervised Road Segmentation
Satoshi Tsutsui, Tommi Kerola, Shunta Saito
We present an approach for road segmentation that only requires image-level annotations at training time. We leverage distant supervision, which allows us to train our model using…