9 Papers were accepted at CVPR 2019, which will be held at Long Beach from June 16-20

Check out the papers below!

  • FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference (Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, Sungroh Yoon)
  • Multi-task Self-Supervised Object Detection via Recycling of Bounding Box Annotations (Wonhee Lee, Joonil Na, Gunhee Kim)
  • End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization (Yeonwoo Jeong, Yoonsung Kim, Hyun Oh Song)
  • Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks (Eunwoo Kim, Chanho Ahn, Philip Torr, Songhwai Oh)
  • Transfer Learning via Unsupervised Task Discovery for Visual Question Answering (Hyeonwoo Noh, Taehoon Kim, Jonghwan Mun, Bohyung Han)
  • Domain Specific Batch Normalization for Unsupervised Domain Adaptation (Woong-Gi Chang, Tackgeun You, Seonguk Seo, Suha Kwak, Bohyung Han)
  • Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences (Seonguk Seo, Paul Hongsuck Seo, Bohyung Han)
  • Streamlined Dense Video Captioning (Jonghwan Mun, Linjie Yang, Zhou Ren, Ning Xu, Bohyung Han)
  • Stochastic Class-based Hard Example Mining for Deep Metric Learning (Yumin Suh, Bohyung Han, Wonsik Kim, Kyoung Mu Lee)