no code implementations • 7 May 2022 • Zhipeng Zhang, Xinglin Hou, Kai Niu, Zhongzhen Huang, Tiezheng Ge, Yuning Jiang, Qi Wu, Peng Wang
Therefore, we present a dataset, E-MMAD (e-commercial multimodal multi-structured advertisement copywriting), which requires, and supports much more detailed information in text generation.
no code implementations • 6 May 2022 • Yiqi Gao, Xinglin Hou, Wei Suo, Mengyang Sun, Tiezheng Ge, Yuning Jiang, Peng Wang
As for the latter, \textbf{\textit{"couple"}} means treating the generation of visual semantic and syntax-related words equally.
no code implementations • 30 Apr 2022 • Min Zhou, Chenchen Xu, Ye Ma, Tiezheng Ge, Yuning Jiang, Weiwei Xu
Through both quantitative and qualitative evaluations, we demonstrate that the proposed model can synthesize high-quality graphic layouts according to image compositions.
no code implementations • 27 Apr 2022 • Yiqi Gao, Xinglin Hou, Yuanmeng Zhang, Tiezheng Ge, Yuning Jiang, Peng Wang
Existing image captioning systems are dedicated to generating narrative captions for images, which are spatially detached from the image in presentation.
no code implementations • 27 Apr 2022 • Gangwei Jiang, Shiyao Wang, Tiezheng Ge, Yuning Jiang, Ying WEI, Defu Lian
The synthetic training images with erasure ground-truth are then fed to train a coarse-to-fine erasing network.
no code implementations • 25 Apr 2022 • Junshan Hu, Chaoxu Guo, Liansheng Zhuang, Biao Wang, Tiezheng Ge, Yuning Jiang, Houqiang Li
For the region perspective, we introduce Region Evaluate Module (REM) which uses a new and efficient sampling method for proposal feature representation containing more contextual information compared with point feature to refine category score and proposal boundary.
1 code implementation • 11 Apr 2022 • Jiale Tao, Biao Wang, Borun Xu, Tiezheng Ge, Yuning Jiang, Wen Li, Lixin Duan
Specifically, inspired by the known deformable part model (DPM), our DAM introduces two types of anchors or keypoints: i) a number of motion anchors that capture both appearance and motion information from the source image and driving video; ii) a latent root anchor, which is linked to the motion anchors to facilitate better learning of the representations of the object structure information.
no code implementations • 10 Apr 2022 • Fanyue Wei, Biao Wang, Tiezheng Ge, Yuning Jiang, Wen Li, Lixin Duan
To this end, we propose to learn pixel-level distinctions to improve the video highlight detection.
no code implementations • 30 Mar 2022 • Xinliang Dai, Yichen Cai, Yuning Jiang, Veit Hagenmeyer
This new variant is characterized by using a reduced modelling method of the distributed AC PF problem, which is reformulated as a zero-residual least-squares problem with consensus constraints.
1 code implementation • 29 Mar 2022 • Peng Yang, Yuning Jiang, Ting Wang, Yong Zhou, Yuanming Shi, Colin N. Jones
To address this issue, in this paper, we instead propose a novel over-the-air second-order federated optimization algorithm to simultaneously reduce the communication rounds and enable low-latency global model aggregation.
no code implementations • 24 Jan 2022 • Wenzhi Fang, Ziyi Yu, Yuning Jiang, Yuanming Shi, Colin N. Jones, Yong Zhou
Under the non-convex setting, we derive the convergence performance of the FedZO algorithm and characterize the impact of the numbers of local iterates and participating edge devices on the convergence.
no code implementations • 19 Dec 2021 • Borun Xu, Biao Wang, Jiale Tao, Tiezheng Ge, Yuning Jiang, Wen Li, Lixin Duan
Creative image animations are attractive in e-commerce applications, where motion transfer is one of the import ways to generate animations from static images.
no code implementations • 1 Dec 2021 • Yingzhao Lian, Yuning Jiang, Naomi Stricker, Lothar Thiele, Colin N. Jones
The wide adoption of wireless devices in the Internet of Things requires controllers that are able to operate with limited resources, such as battery life.
no code implementations • 18 Oct 2021 • Ye Ma, Jin Ma, Min Zhou, Quan Chen, Tiezheng Ge, Yuning Jiang, Tong Lin
Secondly, another GAN model is trained to synthesize real images based on the extended semantic layouts.
no code implementations • 25 May 2021 • Liyi Guo, Junqi Jin, Haoqi Zhang, Zhenzhe Zheng, Zhiye Yang, Zhizhuang Xing, Fei Pan, Lvyin Niu, Fan Wu, Haiyang Xu, Chuan Yu, Yuning Jiang, Xiaoqiang Zhu
To achieve this goal, the advertising platform needs to identify the advertiser's optimization objectives, and then recommend the corresponding strategies to fulfill the objectives.
no code implementations • 11 May 2021 • Wenzhi Fang, Yuning Jiang, Yuanming Shi, Yong Zhou, Wei Chen, Khaled B. Letaief
Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels.
no code implementations • 19 Apr 2021 • Paul Scharnhorst, Emilio T. Maddalena, Yuning Jiang, Colin N. Jones
Let a labeled dataset be given with scattered samples and consider the hypothesis of the ground-truth belonging to the reproducing kernel Hilbert space (RKHS) of a known positive-definite kernel.
no code implementations • CVPR 2021 • Jiacheng Chen, Hexiang Hu, Hao Wu, Yuning Jiang, Changhu Wang
Visual Semantic Embedding (VSE) is a dominant approach for vision-language retrieval, which aims at learning a deep embedding space such that visual data are embedded close to their semantic text labels or descriptions.
no code implementations • 10 Jun 2020 • Yuning Jiang, Junyan Su, Yuanming Shi, Boris Houska
Massive device connectivity in Internet of Thing (IoT) networks with sporadic traffic poses significant communication challenges.
no code implementations • 2 Jun 2020 • Alexander Engelmann, Yuning Jiang, Henrieke Benner, Ruchuan Ou, Boris Houska, Timm Faulwasser
This paper introduces an open-source software for distributed and decentralized non-convex optimization named ALADIN-$\alpha$.
2 code implementations • CVPR 2020 • Yifang Men, Yiming Mao, Yuning Jiang, Wei-Ying Ma, Zhouhui Lian
This paper introduces the Attribute-Decomposed GAN, a novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes (e. g., pose, head, upper clothes and pants) provided in various source inputs.
Ranked #6 on
Pose Transfer
on Deep-Fashion
no code implementations • 17 Feb 2020 • Hao Wu, Hanyuan Zhang, Xin-Yu Zhang, Weiwei Sun, Baihua Zheng, Yuning Jiang
We propose a deep convolutional neural network called DeepDualMapper which fuses the aerial image and trajectory data in a more seamless manner to extract the digital map.
no code implementations • ICLR 2020 • Tao Kong, Fuchun Sun, Huaping Liu, Yuning Jiang, Lei LI, Jianbo Shi
While almost all state-of-the-art object detectors utilize predefined anchors to enumerate possible locations, scales and aspect ratios for the search of the objects, their performance and generalization ability are also limited to the design of anchors.
22 code implementations • ECCV 2020 • Xinlong Wang, Tao Kong, Chunhua Shen, Yuning Jiang, Lei LI
We present a new, embarrassingly simple approach to instance segmentation in images.
Ranked #34 on
Instance Segmentation
on COCO test-dev
1 code implementation • 17 Sep 2019 • Xinlong Wang, Wei Yin, Tao Kong, Yuning Jiang, Lei LI, Chunhua Shen
In this paper, we first analyse the data distributions and interaction of foreground and background, then propose the foreground-background separated monocular depth estimation (ForeSeE) method, to estimate the foreground depth and background depth using separate optimization objectives and depth decoders.
no code implementations • 5 Sep 2019 • Zhichen Zhao, Bo-Wen Zhang, Yuning Jiang, Li Xu, Lei LI, Wei-Ying Ma
However, the datasets from source domain are simply discarded in the fine-tuning process.
1 code implementation • 11 Apr 2019 • Hao Wu, Jiayuan Mao, Yufeng Zhang, Yuning Jiang, Lei LI, Weiwei Sun, Wei-Ying Ma
We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a joint space of visual and textual concepts.
6 code implementations • 8 Apr 2019 • Tao Kong, Fuchun Sun, Huaping Liu, Yuning Jiang, Lei LI, Jianbo Shi
In FoveaBox, an instance is assigned to adjacent feature levels to make the model more accurate. We demonstrate its effectiveness on standard benchmarks and report extensive experimental analysis.
Ranked #93 on
Object Detection
on COCO test-dev
(APM metric)
no code implementations • 19 Jan 2019 • Tao Kong, Fuchun Sun, Huaping Liu, Yuning Jiang, Jianbo Shi
We present consistent optimization for single stage object detection.
4 code implementations • ECCV 2018 • Borui Jiang, Ruixuan Luo, Jiayuan Mao, Tete Xiao, Yuning Jiang
The network acquires this confidence of localization, which improves the NMS procedure by preserving accurately localized bounding boxes.
Ranked #153 on
Object Detection
on COCO test-dev
19 code implementations • ECCV 2018 • Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, Jian Sun
In this paper, we study a new task called Unified Perceptual Parsing, which requires the machine vision systems to recognize as many visual concepts as possible from a given image.
Ranked #67 on
Semantic Segmentation
on ADE20K val
1 code implementation • COLING 2018 • Haoyue Shi, Jiayuan Mao, Tete Xiao, Yuning Jiang, Jian Sun
Begin with an insightful adversarial attack on VSE embeddings, we show the limitation of current frameworks and image-text datasets (e. g., MS-COCO) both quantitatively and qualitatively.
2 code implementations • CVPR 2018 • Xinlong Wang, Tete Xiao, Yuning Jiang, Shuai Shao, Jian Sun, Chunhua Shen
In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the crowd occlusion problem.
Ranked #7 on
Pedestrian Detection
on Caltech
(using extra training data)
6 code implementations • CVPR 2018 • Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, Jian Sun
The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network, new framework, or novel loss design.
no code implementations • CVPR 2017 • Jiayuan Mao, Tete Xiao, Yuning Jiang, Zhimin Cao
Aggregating extra features has been considered as an effective approach to boost traditional pedestrian detection methods.
Ranked #13 on
Pedestrian Detection
on Caltech
3 code implementations • CVPR 2017 • Hexiang Hu, Shiyi Lan, Yuning Jiang, Zhimin Cao, Fei Sha
Objects appear to scale differently in natural images.
no code implementations • 4 Aug 2016 • Jiahui Yu, Yuning Jiang, Zhangyang Wang, Zhimin Cao, Thomas Huang
In present object detection systems, the deep convolutional neural networks (CNNs) are utilized to predict bounding boxes of object candidates, and have gained performance advantages over the traditional region proposal methods.
no code implementations • 12 Mar 2014 • Haoqiang Fan, Zhimin Cao, Yuning Jiang, Qi Yin, Chinchilla Doudou
Our basic network is capable of achieving high recognition accuracy ($85. 8\%$ on LFW benchmark) with only 8 dimension representation.