Search Results for author: Mengmeng Wang

Found 30 papers, 10 papers with code

Adjacent-level Feature Cross-Fusion with 3D CNN for Remote Sensing Image Change Detection

1 code implementation10 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.

Change Detection

Exploiting Neighborhood Structural Features for Change Detection

no code implementations10 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.

Change Detection

Learning Discretized Neural Networks under Ricci Flow

no code implementations7 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.

Revisiting the Spatial and Temporal Modeling for Few-shot Action Recognition

no code implementations19 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.

Few-Shot action recognition Few Shot Action Recognition

BSNet: Lane Detection via Draw B-spline Curves Nearby

no code implementations17 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.

Lane Detection

E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context

1 code implementation17 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.

Dynamically Stable Poincaré Embeddings for Neural Manifolds

no code implementations21 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.

Image Classification

A Simple Long-Tailed Recognition Baseline via Vision-Language Model

1 code implementation29 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)

Contrastive Learning Language Modelling +3

MaIL: A Unified Mask-Image-Language Trimodal Network for Referring Image Segmentation

no code implementations21 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.

Image Segmentation Referring Expression Segmentation +1

Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking

no code implementations28 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.

Contrastive Learning Visual Object Tracking +1

ActionCLIP: A New Paradigm for Video Action Recognition

2 code implementations17 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".

Action Classification Action Recognition In Videos +4

Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation

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.

Monocular Depth Estimation

TransVOS: Video Object Segmentation with Transformers

1 code implementation1 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

One-shot Face Reenactment Using Appearance Adaptive Normalization

no code implementations8 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.

Face Reenactment

Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation

no code implementations5 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.

Image Generation

RFNet: Recurrent Forward Network for Dense Point Cloud Completion

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.

Point Cloud Completion

FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion

no code implementations15 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.

Depth Completion

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

1 code implementation14 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.

Monocular Depth Estimation Self-Supervised Learning

Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition

no code implementations15 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.

Action Recognition Knowledge Distillation +1

Semantic Graph Based Place Recognition for 3D Point Clouds

1 code implementation26 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.

Graph Matching Graph Similarity

The 'Letter' Distribution in the Chinese Language

no code implementations26 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.

Realistic Face Reenactment via Self-Supervised Disentangling of Identity and Pose

no code implementations29 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.

Face Reenactment

Extended Feature Pyramid Network for Small Object Detection

1 code implementation16 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.

object-detection Small Object Detection

FReeNet: Multi-Identity Face Reenactment

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.

Face Reenactment

Real-time 3D Human Tracking for Mobile Robots with Multisensors

no code implementations15 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).

Visual Tracking

Large Margin Object Tracking with Circulant Feature Maps

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.

Object Tracking

Robust Object Tracking with a Hierarchical Ensemble Framework

no code implementations23 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.

Object Tracking

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