57 citations · 80 across the 11 of their papers we have counts for
5 papers · 1 filter
Fully Self-Supervised Learning for Semantic Segmentation
Yuan Wang, Wei Zhuo, Yucong Li +3
In this work, we present a fully self-supervised framework for semantic segmentation(FS^4). A fully bootstrapped strategy for semantic segmentation, which saves efforts for the hug…
Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation
Ke Zhang, Sihong Chen, Qi Ju +3
With the increase in the number of image data and the lack of corresponding labels, weakly supervised learning has drawn a lot of attention recently in computer vision tasks, espec…
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection
Pei Xu, Shan Huang, Hongzhen Wang +3
Chinese keyword spotting is a challenging task as there is no visual blank for Chinese words. Different from English words which are split naturally by visual blanks, Chinese words…
RefineDetLite: A Lightweight One-stage Object Detection Framework for CPU-only Devices
Chen Chen, Mengyuan Liu, Xiandong Meng +2
Previous state-of-the-art real-time object detectors have been reported on GPUs which are extremely expensive for processing massive data and in resource-restricted scenarios. Ther…
Improving Image Captioning with Conditional Generative Adversarial Nets
Chen Chen, Shuai Mu, Wanpeng Xiao +3
In this paper, we propose a novel conditional-generative-adversarial-nets-based image captioning framework as an extension of traditional reinforcement-learning (RL)-based encoder-…