no code implementations • 7 Sep 2023 • Li Li, Qingqing Li, Guozheng Xu, Pengwei Zhou, Jingmin Tu, Jie Li, Jian Yao
We design a three-branch network to predict semantic labels, point offsets and extract deep embedding features.
no code implementations • 25 Dec 2022 • Chao Hu, Jian Yao, Weijie Wu, Weibin Qiu, Liqiang Zhu
Currently, most deep learning methods cannot solve the problem of scarcity of industrial product defect samples and significant differences in characteristics.
1 code implementation • 23 Oct 2022 • Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang
The key intuition is that the occluded part of an object can be explained away if that part is visible in other frames, possibly deformed as long as the deformation can be reasonably learned.
no code implementations • 11 Oct 2022 • Yuxi Xiao, Li Li, Xiaodi Li, Jian Yao
In addition, in order to increase the robustness of our framework, we formulate the likelihood function of the correlations of 2D image matches as a Gaussian and Uniform mixture distribution which takes the uncertainty caused by illumination changes, image noise and moving objects into account.
no code implementations • 4 Mar 2022 • Haonan Dong, Jian Yao
Though nowadays unsupervised learning methods have been proposed and have gotten gratifying results, those methods still fail to reconstruct intact results in challenging scenes, such as weakly-textured surfaces, as those methods primarily depend on pixel-wise photometric consistency which is subjected to various illuminations.
no code implementations • NeurIPS 2021 • Longyuan Li, Jian Yao, Li Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang
Learning the distribution of future trajectories conditioned on the past is a crucial problem for understanding multi-agent systems.
2 code implementations • 26 Mar 2021 • Puyuan Yi, Shengkun Tang, Jian Yao
Distinct from these approaches, we propose a Dynamic Depth Range Network (DDR-Net) to determine the depth range hypotheses dynamically by applying a range estimation module (REM) to learn the uncertainties of range hypotheses in the former stages.
no code implementations • 8 Jul 2020 • Zheyuan Xu, Hongche Yin, Jian Yao
To tackle this issue, in this paper, we propose a deformable spatial propagation network (DSPN) to adaptively generates different receptive field and affinity matrix for each pixel.
no code implementations • 6 Apr 2020 • Kai Chen, Jian Yao, Jingmin Tu, Yahui Liu, Yinxuan Li, Li Li
Recently, works on improving the naturalness of stitching images gain more and more extensive attention.
1 code implementation • 15 Mar 2020 • Yahui Liu, Marco De Nadai, Jian Yao, Nicu Sebe, Bruno Lepri, Xavier Alameda-Pineda
Unsupervised image-to-image translation (UNIT) aims at learning a mapping between several visual domains by using unpaired training images.
no code implementations • 21 Aug 2019 • Jian Yao, Ahmad Al-Dahle
However, due to the large variance of the enhanced speech with even the same cosine similarity loss in high dimensional space, a deep neural network learnt with this loss might not be able to predict enhanced speech with good quality.
1 code implementation • EMNLP 2018 • Yahui Liu, Wei Bi, Jun Gao, Xiaojiang Liu, Jian Yao, Shuming Shi
We observe that in the conversation tasks, each query could have multiple responses, which forms a 1-to-n or m-to-n relationship in the view of the total corpus.
no code implementations • 18 Sep 2018 • Kai Chen, Jingmin Tu, Binbin Xiang, Li Li, Jian Yao
In this paper, geometric and photometric constraints are combined to improve the alignment quality, which is based on the observation that these two kinds of constraints are complementary.
no code implementations • 18 Sep 2018 • Kai Chen, Jingmin Tu, Jian Yao
Content-Preserving Warping (CPW) is a typical method to deal with this issue, in which geometric and photometric constraints are imposed to guide the warping process.
no code implementations • 4 Apr 2018 • Xinpeng Chen, Jingyuan Chen, Lin Ma, Jian Yao, Wei Liu, Jiebo Luo, Tong Zhang
First, we demonstrate that video attractiveness and different engagements present different relationships.
1 code implementation • CVPR 2018 • Xinpeng Chen, Lin Ma, Wenhao Jiang, Jian Yao, Wei Liu
Recently, caption generation with an encoder-decoder framework has been extensively studied and applied in different domains, such as image captioning, code captioning, and so on.
no code implementations • 12 May 2017 • Yahui Liu, Jian Yao, Li Li, Xiaohu Lu, Jing Han
We develop a novel deep contour detection algorithm with a top-down fully convolutional encoder-decoder network.
1 code implementation • 31 Mar 2016 • Tong He, Weilin Huang, Yu Qiao, Jian Yao
We propose a novel Cascaded Convolutional Text Network (CCTN) that joints two customized convolutional networks for coarse-to-fine text localization.
no code implementations • IEEE Trans. on Image Processing, 2016 2016 • Tong He, Weilin Huang, Yu Qiao, Jian Yao
Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images.
no code implementations • 12 Oct 2015 • Tong He, Weilin Huang, Yu Qiao, Jian Yao
The rich supervision information enables the Text-CNN with a strong capability for discriminating ambiguous texts, and also increases its robustness against complicated background components.
no code implementations • CVPR 2015 • Mi Zhang, Jian Yao, Menghan Xia, Kai Li, Yi Zhang, Yaping Liu
Fisheye image rectification and estimation of intrinsic parameters for real scenes have been addressed in the literature by using line information on the distorted images.
no code implementations • CVPR 2015 • Jian Yao, Marko Boben, Sanja Fidler, Raquel Urtasun
In this paper, we tackle the problem of unsupervised segmentation in the form of superpixels.
no code implementations • CVPR 2013 • Roozbeh Mottaghi, Sanja Fidler, Jian Yao, Raquel Urtasun, Devi Parikh
Recent trends in semantic image segmentation have pushed for holistic scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape analysis, contextual reasoning.