1 code implementation • CVPR 2021 • Zhihao Liu, Hui Yin, Xinyi Wu, Zhenyao Wu, Yang Mi, Song Wang
Shadow removal is a computer-vision task that aims to restore the image content in shadow regions.
1 code implementation • 28 Jun 2020 • Zhihao Liu, Hui Yin, Yang Mi, Mengyang Pu, Song Wang
In this paper, we present a new Lightness-Guided Shadow Removal Network (LG-ShadowNet) for shadow removal by training on unpaired data.
no code implementations • 13 May 2019 • Tianxiao Zhao, Chunbo Luo, Geyong Min, Jianming Zhou, Dechun Guo, Wang Miao, Yang Mi
Then, we propose a DoA estimation algorithm and a steering vector adaptive receiving beam forming method.
1 code implementation • CVPR 2019 • Sen He, Hamed R. -Tavakoli, Ali Borji, Yang Mi, Nicolas Pugeault
Our analyses reveal that: 1) some visual regions (e. g. head, text, symbol, vehicle) are already encoded within various layers of the network pre-trained for object recognition, 2) using modern datasets, we find that fine-tuning pre-trained models for saliency prediction makes them favor some categories (e. g. head) over some others (e. g. text), 3) although deep models of saliency outperform classical models on natural images, the converse is true for synthetic stimuli (e. g. pop-out search arrays), an evidence of significant difference between human and data-driven saliency models, and 4) we confirm that, after-fine tuning, the change in inner-representations is mostly due to the task and not the domain shift in the data.
no code implementations • 15 Mar 2018 • Sen He, Ali Borji, Yang Mi, Nicolas Pugeault
Deep convolutional neural networks have demonstrated high performances for fixation prediction in recent years.
no code implementations • 15 Mar 2018 • Sen He, Dmitry Kangin, Yang Mi, Nicolas Pugeault
In this paper, we apply the attention mechanism to autonomous driving for steering angle prediction.
no code implementations • 20 Nov 2017 • Weiyao Lin, Yang Mi, Jianxin Wu, Ke Lu, Hongkai Xiong
In this paper, we propose a novel deep-based framework for action recognition, which improves the recognition accuracy by: 1) deriving more precise features for representing actions, and 2) reducing the asynchrony between different information streams.
no code implementations • CVPR 2016 • Hongkai Yu, Youjie Zhou, Jeff Simmons, Craig P. Przybyla, Yuewei Lin, Xiaochuan Fan, Yang Mi, Song Wang
In particular, the within-group association is modeled by a nonrigid 2D Thin-Plate transform and a sequence of group shrinking, group growing and group merging operations are then developed to refine the composition of each group.
no code implementations • 16 Feb 2016 • Weiyao Lin, Yang Mi, Weiyue Wang, Jianxin Wu, Jingdong Wang, Tao Mei
These semantic regions can be used to recognize pre-defined activities in crowd scenes.