no code implementations • 11 Mar 2022 • Jie Ma, Yalong Bai, Bineng Zhong, Wei zhang, Ting Yao, Tao Mei
Vision Transformer (ViT) has become a leading tool in various computer vision tasks, owing to its unique self-attention mechanism that learns visual representations explicitly through cross-patch information interactions.
1 code implementation • 25 Sep 2021 • Qinglin Liu, Haozhe Xie, Shengping Zhang, Bineng Zhong, Rongrong Ji
Finally, we use the matting module which takes the image, trimap and context features to estimate the alpha matte.
Ranked #2 on Image Matting on Composition-1K (using extra training data)
1 code implementation • CVPR 2021 • Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji
In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.
1 code implementation • CVPR 2021 • Zikai Zhang, Bineng Zhong, Shengping Zhang, Zhenjun Tang, Xin Liu, Zhaoxiang Zhang
A practical long-term tracker typically contains three key properties, i. e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness mechanism.
1 code implementation • CVPR 2021 • Siyuan Cheng, Bineng Zhong, Guorong Li, Xin Liu, Zhenjun Tang, Xianxian Li, Jing Wang
RD performs in a meta-learning way to obtain a learning ability to filter the distractors from the background while RM aims to effectively integrate the proposed RD into the Siamese framework to generate accurate tracking result.
no code implementations • ICCV 2021 • Qinqin Zhou, Xiawu Zheng, Liujuan Cao, Bineng Zhong, Teng Xi, Gang Zhang, Errui Ding, Mingliang Xu, Rongrong Ji
EC-DARTS decouples different operations based on their categories to optimize the operation weights so that the operation gap between them is shrinked.
1 code implementation • CVPR 2020 • Jie Li, Rongrong Ji, Hong Liu, Jianzhuang Liu, Bineng Zhong, Cheng Deng, Qi Tian
For reducing the solution space, we first model the adversarial perturbation optimization problem as a process of recovering frequency-sparse perturbations with compressed sensing, under the setting that random noise in the low-frequency space is more likely to be adversarial.
no code implementations • CVPR 2020 • Jiahua Dong, Yang Cong, Gan Sun, Bineng Zhong, Xiaowei Xu
Unsupervised domain adaptation has attracted growing research attention on semantic segmentation.
2 code implementations • CVPR 2020 • Zedu Chen, Bineng Zhong, Guorong Li, Shengping Zhang, Rongrong Ji
Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target.
2 code implementations • ICLR 2019 • Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, Yun Fu
To address this issue, we design local and non-local attention blocks to extract features that capture the long-range dependencies between pixels and pay more attention to the challenging parts.
no code implementations • 6 Mar 2019 • Gan Sun, Yang Cong, Qianqian Wang, Bineng Zhong, Yun Fu
Consider the lifelong machine learning paradigm whose objective is to learn a sequence of tasks depending on previous experiences, e. g., knowledge library or deep network weights.
2 code implementations • 25 Dec 2018 • Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, Yun Fu
We fully exploit the hierarchical features from all the convolutional layers.
18 code implementations • ECCV 2018 • Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, Yun Fu
To solve these problems, we propose the very deep residual channel attention networks (RCAN).
Ranked #14 on Image Super-Resolution on BSD100 - 4x upscaling
no code implementations • ICLR 2019 • Jun Li, Hongfu Liu, Bineng Zhong, Yue Wu, Yun Fu
To address this problem, we propose a simple yet effective method for improving stochastic gradient methods named predictive local smoothness (PLS).
13 code implementations • CVPR 2018 • Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, Yun Fu
In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR. We fully exploit the hierarchical features from all the convolutional layers.
Ranked #3 on Color Image Denoising on CBSD68 sigma50
no code implementations • 25 Mar 2016 • Yan Yan, Hanzi Wang, Cuihua Li, Chenhui Yang, Bineng Zhong
In this paper, an effective unconstrained correlation filter called Uncon- strained Optimal Origin Tradeoff Filter (UOOTF) is presented and applied to robust face recognition.
no code implementations • CVPR 2015 • Xian-Ming Liu, Rongrong Ji, Changhu Wang, Wei Liu, Bineng Zhong, Thomas S. Huang
A hierarchical shape parsing strategy is proposed to partition and organize image components into a hierarchical structure in the scale space.