In this story, Pyramid Attention Network for Semantic Segmentation, (PAN), by Beijing Institute of Technology, Megvii Inc. (Face++), and Peking University, is reviewed. In this paper:
This is a paper in 2018 BMVC with over 200 citations. (Sik-Ho Tsang @ Medium)
In this story, Learning from Simulated and Unsupervised Images through Adversarial Training, (SimGAN), by Apple Inc., is reviewed. In this paper:
This is a paper in 2017 CVPR with over 1300 citations. (Sik-Ho Tsang @ Medium)
In this story, CenterNet: Keypoint Triplets for Object Detection, (CenterNet), by University of Chinese Academy of Sciences, Huazhong University of Science and Technology, Huawei Noah’s Ark Lab, CAS, and Peng Cheng Laboratory, is reviewed. In this story:
In this story, Unsupervised Image-to-Image Translation Networks, (UNIT), by NVIDIA, is reviewed. In this paper:
This is a paper in 2017 NIPS with over 1500 citations. (Sik-Ho Tsang @ Medium)
In this story, CornerNet: Detecting Objects as Paired Keypoints, (CornerNet), by University of Michigan, is reviewed. In this paper:
This is a paper in 2018 ECCV with over 900 citations. (Sik-Ho Tsang @ Medium)
In this story, Single-Shot Refinement Neural Network for Object Detection, (RefineDet), by Chinese Academy of Sciences, University of Chinese Academy of Sciences, and GE Global Research, is reviewed. In this paper:
In this story, CoupleNet: Coupling Global Structure with Local Parts for Object Detection, (CoupleNet), by Chinese Academy of Sciences, University of Chinese Academy of Sciences, Nanjing Audit University, and Indiana University, is reviewed. In this paper:
In this story, A Comprehensive Benchmark for Single Image Compression Artifact Reduction, (LIU4K), by Peking University, and University of Science and Technology of China, is reviewed. In this paper:
This is a paper in 2020 TIP where TIP has a high impact factor of 9.34. (Sik-Ho Tsang @ Medium)
In this story, Training Region-based Object Detectors with Online Hard Example Mining, (OHEM), by Carnegie Mellon University, and Facebook AI Research (FAIR), is reviewed.
Detection datasets contain an overwhelming number of easy examples and a small number of hard examples.
In this paper:
This is a paper in 2016 CVPR with over 1300 citations. (Sik-Ho Tsang @ Medium)
In this story, Coupled Generative Adversarial Networks, (CoGAN), by Mitsubishi Electric Research Labs (MERL), is reviewed.
The paper concerns the problem of learning a joint distribution of multi-domain images from data.
In this paper:
This is a paper in 2016 NIPS with over 1100 citations. (Sik-Ho Tsang @ Medium)
PhD, Researcher. I share what I've learnt and done. :) My LinkedIn: https://www.linkedin.com/in/sh-tsang/, My Paper Reading List: https://bit.ly/33TDhxG