no code implementations • 15 Mar 2023 • Zizhang Li, Xiaoyang Lyu, Yuanyuan Ding, Mengmeng Wang, Yiyi Liao, Yong liu
Recently, neural implicit surfaces have become popular for multi-view reconstruction.
1 code implementation • 10 Feb 2023 • Yuanxin Ye, Mengmeng Wang, Liang Zhou, Guangyang Lei, Jianwei Fan, Yao Qin
First, through the inner fusion property of 3D convolution, we design a new feature fusion way that can simultaneously extract and fuse the feature information from bi-temporal images.
no code implementations • 10 Feb 2023 • Mengmeng Wang, Zhiqiang Han, Peizhen Yang, Bai Zhu, Ming Hao, Jianwei Fan, Yuanxin Ye
In this letter, a novel method for change detection is proposed using neighborhood structure correlation.
no code implementations • 7 Feb 2023 • Jun Chen, Hanwen Chen, Mengmeng Wang, Guang Dai, Yong liu
We propose an analysis that this mismatch can be viewed as a metric perturbation in a Riemannian manifold through the lens of duality theory.
no code implementations • 19 Jan 2023 • Jiazheng Xing, Mengmeng Wang, Boyu Mu, Yong liu
In this paper, we propose SloshNet, a new framework that revisits the spatial and temporal modeling for few-shot action recognition in a finer manner.
no code implementations • 17 Jan 2023 • Haoxin Chen, Mengmeng Wang, Yong liu
The locality of lane representation is the ability to modify lanes locally which can simplify parameter optimization.
1 code implementation • 17 Jul 2022 • Zizhang Li, Mengmeng Wang, Huaijin Pi, Kechun Xu, Jianbiao Mei, Yong liu
However, the redundant parameters within the network structure can cause a large model size when scaling up for desirable performance.
no code implementations • 21 Dec 2021 • Jun Chen, Yuang Liu, Xiangrui Zhao, Mengmeng Wang, Yong liu
As a result, we prove that, if initial metrics have an $L^2$-norm perturbation which deviates from the Hyperbolic metric on the Poincar\'e ball, the scaled Ricci-DeTurck flow of such metrics smoothly and exponentially converges to the Hyperbolic metric.
1 code implementation • 29 Nov 2021 • Teli Ma, Shijie Geng, Mengmeng Wang, Jing Shao, Jiasen Lu, Hongsheng Li, Peng Gao, Yu Qiao
Recent advances in large-scale contrastive visual-language pretraining shed light on a new pathway for visual recognition.
Ranked #2 on
Long-tail Learning
on Places-LT
(using extra training data)
no code implementations • 21 Nov 2021 • Zizhang Li, Mengmeng Wang, Jianbiao Mei, Yong liu
Referring image segmentation is a typical multi-modal task, which aims at generating a binary mask for referent described in given language expressions.
Ranked #1 on
Referring Expression Segmentation
on G-Ref test B
no code implementations • 28 Oct 2021 • Mengmeng Wang, Xiaoqian Yang, Yong liu
Visual object tracking performance has been dramatically improved in recent years, but some severe challenges remain open, like distractors and occlusions.
2 code implementations • 17 Sep 2021 • Mengmeng Wang, Jiazheng Xing, Yong liu
Moreover, to handle the deficiency of label texts and make use of tremendous web data, we propose a new paradigm based on this multimodal learning framework for action recognition, which we dub "pre-train, prompt and fine-tune".
Ranked #2 on
Action Recognition In Videos
on Kinetics-400
2 code implementations • ICCV 2021 • Lina Liu, Xibin Song, Mengmeng Wang, Yong liu, Liangjun Zhang
Meanwhile, to guarantee that the day and night images contain the same information, the domain-separated network takes the day-time images and corresponding night-time images (generated by GAN) as input, and the private and invariant feature extractors are learned by orthogonality and similarity loss, where the domain gap can be alleviated, thus better depth maps can be expected.
1 code implementation • 1 Jun 2021 • Jianbiao Mei, Mengmeng Wang, Yeneng Lin, Yi Yuan, Yong liu
Recently, Space-Time Memory Network (STM) based methods have achieved state-of-the-art performance in semi-supervised video object segmentation (VOS).
One-shot visual object segmentation
Semantic Segmentation
+1
no code implementations • 8 Feb 2021 • Guangming Yao, Yi Yuan, Tianjia Shao, Shuang Li, Shanqi Liu, Yong liu, Mengmeng Wang, Kun Zhou
The paper proposes a novel generative adversarial network for one-shot face reenactment, which can animate a single face image to a different pose-and-expression (provided by a driving image) while keeping its original appearance.
no code implementations • 5 Feb 2021 • Jilin Tang, Yi Yuan, Tianjia Shao, Yong liu, Mengmeng Wang, Kun Zhou
In this paper we tackle the problem of pose guided person image generation, which aims to transfer a person image from the source pose to a novel target pose while maintaining the source appearance.
no code implementations • ICCV 2021 • Tianxin Huang, Hao Zou, Jinhao Cui, Xuemeng Yang, Mengmeng Wang, Xiangrui Zhao, Jiangning Zhang, Yi Yuan, Yifan Xu, Yong liu
The RFE extracts multiple global features from the incomplete point clouds for different recurrent levels, and the FDC generates point clouds in a coarse-to-fine pipeline.
no code implementations • 15 Dec 2020 • Lina Liu, Xibin Song, Xiaoyang Lyu, Junwei Diao, Mengmeng Wang, Yong liu, Liangjun Zhang
Then, a refined depth map is further obtained using a residual learning strategy in the coarse-to-fine stage with a coarse depth map and color image as input.
1 code implementation • 14 Dec 2020 • Xiaoyang Lyu, Liang Liu, Mengmeng Wang, Xin Kong, Lina Liu, Yong liu, Xinxin Chen, Yi Yuan
To obtainmore accurate depth estimation in large gradient regions, itis necessary to obtain high-resolution features with spatialand semantic information.
no code implementations • 15 Sep 2020 • Haisheng Su, Jing Su, Dongliang Wang, Weihao Gan, Wei Wu, Mengmeng Wang, Junjie Yan, Yu Qiao
Second, the parameter frequency distribution is further adopted to guide the student network to learn the appearance modeling process from the teacher.
1 code implementation • 26 Aug 2020 • Xin Kong, Xuemeng Yang, Guangyao Zhai, Xiangrui Zhao, Xianfang Zeng, Mengmeng Wang, Yong liu, Wanlong Li, Feng Wen
First, we propose a novel semantic graph representation for the point cloud scenes by reserving the semantic and topological information of the raw point cloud.
1 code implementation • ECCV 2020 • Jiangning Zhang, Chao Xu, Liang Liu, Mengmeng Wang, Xia Wu, Yong liu, Yunliang Jiang
The proposed DTVNet consists of two submodules: \emph{Optical Flow Encoder} (OFE) and \emph{Dynamic Video Generator} (DVG).
no code implementations • 26 May 2020 • Qinghua Chen, Yan Wang, Mengmeng Wang, Xiaomeng Li
In addition, we collected Chinese literature corpora for different historical periods from the Tang Dynasty to the present, and we dismantled the Chinese written language into three kinds of basic particles: characters, strokes and constructive parts.
no code implementations • 29 Mar 2020 • Xianfang Zeng, Yusu Pan, Mengmeng Wang, Jiangning Zhang, Yong liu
On the one hand, we adopt the deforming autoencoder to disentangle identity and pose representations.
1 code implementation • 16 Mar 2020 • Chunfang Deng, Mengmeng Wang, Liang Liu, Yong liu
Small object detection remains an unsolved challenge because it is hard to extract information of small objects with only a few pixels.
no code implementations • ICCV 2019 • Boyuan Jiang, Mengmeng Wang, Weihao Gan, Wei Wu, Junjie Yan
Spatiotemporal and motion features are two complementary and crucial information for video action recognition.
Ranked #1 on
Action Recognition In Videos
on HMDB-51
no code implementations • CVPR 2020 • Jiangning Zhang, Xianfang Zeng, Mengmeng Wang, Yusu Pan, Liang Liu, Yong liu, Yu Ding, Changjie Fan
This paper presents a novel multi-identity face reenactment framework, named FReeNet, to transfer facial expressions from an arbitrary source face to a target face with a shared model.
no code implementations • 15 Mar 2017 • Mengmeng Wang, Daobilige Su, Lei Shi, Yong liu, Jaime Valls Miro
An ultrasonic sensor array is employed to provide the range information from the target person to the robot and Gaussian Process Regression is used for partial location estimation (2-D).
no code implementations • CVPR 2017 • Mengmeng Wang, Yong liu, Zeyi Huang
Structured output support vector machine (SVM) based tracking algorithms have shown favorable performance recently.
no code implementations • 23 Sep 2015 • Mengmeng Wang, Yong liu
A discriminative model which accounts for the matching degree of local patches is adopted via a bottom ensemble layer, and a generative model which exploits holistic templates is used to search for the object through the middle ensemble layer as well as an adaptive Kalman filter.