48 citations · 91 across the 4 of their papers we have counts for
4 papers
Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation
Guangchen Shi, Yirui Wu, Jun Liu +3
Incremental few-shot semantic segmentation (IFSS) targets at incrementally expanding model's capacity to segment new class of images supervised by only a few samples. However, feat…
Perceptual Image Super-Resolution with Progressive Adversarial Network
Lone Wong, Deli Zhao, Shaohua Wan +1
Single Image Super-Resolution (SISR) aims to improve resolution of small-size low-quality image from a single one. With popularity of consumer electronics in our daily life, this t…
A Matrix-in-matrix Neural Network for Image Super Resolution
Hailong Ma, Xiangxiang Chu, Bo Zhang +1
In recent years, deep learning methods have achieved impressive results with higher peak signal-to-noise ratio in single image super-resolution (SISR) tasks by utilizing deeper lay…
Bootstrapping Face Detection with Hard Negative Examples
Shaohua Wan, Zhijun Chen, Tao Zhang +2
Recently significant performance improvement in face detection was made possible by deeply trained convolutional networks. In this report, a novel approach for training state-of-th…