Search Results for author: Qiu Shen

Found 17 papers, 8 papers with code

MMVP: A Multimodal MoCap Dataset with Vision and Pressure Sensors

no code implementations26 Mar 2024 He Zhang, Shenghao Ren, Haolei Yuan, Jianhui Zhao, Fan Li, Shuangpeng Sun, Zhenghao Liang, Tao Yu, Qiu Shen, Xun Cao

To validate the dataset, we propose an RGBD-P SMPL fitting method and also a monocular-video-based baseline framework, VP-MoCap, for human motion capture.


RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets

1 code implementation16 Oct 2023 Zhicheng Cai, Xiaohan Ding, Qiu Shen, Xun Cao

We propose Re-parameterized Refocusing Convolution (RefConv) as a replacement for regular convolutional layers, which is a plug-and-play module to improve the performance without any inference costs.

Image Classification object-detection +2

Learn to Enhance the Negative Information in Convolutional Neural Network

no code implementations18 Jun 2023 Zhicheng Cai, Chenglei Peng, Qiu Shen

In this way, LENI can enhance the model representational capacity significantly while maintaining the original advantages of ReLU.

FalconNet: Factorization for the Light-weight ConvNets

no code implementations10 Jun 2023 Zhicheng Cai, Qiu Shen

To address these issues, we factorize the four vital components of light-weight CNNs from coarse to fine and redesign them: i) we design a light-weight overall architecture termed LightNet, which obtains better performance by simply implementing the basic blocks of other light-weight CNNs; ii) we abstract a Meta Light Block, which consists of spatial operator and channel operator and uniformly describes current basic blocks; iii) we raise RepSO which constructs multiple spatial operator branches to enhance the representational ability; iv) we raise the concept of receptive range, guided by which we raise RefCO to sparsely factorize the channel operator.

Explore Spatio-temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline

1 code implementation CVPR 2022 Kailai Zhou, Yibo Wang, Tao Lv, Yunqian Li, Linsen Chen, Qiu Shen, Xun Cao

We endeavor on a rarely explored task named Insubstantial Object Detection (IOD), which aims to localize the object with following characteristics: (1) amorphous shape with indistinct boundary; (2) similarity to surroundings; (3) absence in color.

object-detection Object Detection

FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction

1 code implementation1 Nov 2021 Hao Zhu, Haotian Yang, Longwei Guo, Yidi Zhang, Yanru Wang, Mingkai Huang, Menghua Wu, Qiu Shen, Ruigang Yang, Xun Cao

By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input.

3D Face Reconstruction 3D Reconstruction

Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition

1 code implementation CVPR 2021 Jiahui She, Yibo Hu, Hailin Shi, Jun Wang, Qiu Shen, Tao Mei

Due to the subjective annotation and the inherent interclass similarity of facial expressions, one of key challenges in Facial Expression Recognition (FER) is the annotation ambiguity.

Facial Expression Recognition Facial Expression Recognition (FER)

Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image

no code implementations18 Dec 2020 Yuxing Huang, ShaoDi You, Ying Fu, Qiu Shen

It is based on the idea that high-resolution HSIs in city scenes contain rich spectral information, which can be easily associated to semantics without manual labeling.

Segmentation Semi-Supervised Semantic Segmentation +2

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

1 code implementation CVPR 2020 Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input.

Neural Image Compression via Non-Local Attention Optimization and Improved Context Modeling

1 code implementation11 Oct 2019 Tong Chen, Haojie Liu, Zhan Ma, Qiu Shen, Xun Cao, Yao Wang

This paper proposes a novel Non-Local Attention optmization and Improved Context modeling-based image compression (NLAIC) algorithm, which is built on top of the deep nerual network (DNN)-based variational auto-encoder (VAE) structure.

Image Compression MS-SSIM +1

Learned Point Cloud Geometry Compression

2 code implementations26 Sep 2019 Jianqiang Wang, Hao Zhu, Zhan Ma, Tong Chen, Haojie Liu, Qiu Shen

This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a. k. a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep neural networks (DNN) based variational autoencoders (VAE).

Surface Reconstruction

Hyperspectral City V1.0 Dataset and Benchmark

no code implementations24 Jul 2019 Shaodi You, Erqi Huang, Shuaizhe Liang, Yongrong Zheng, Yunxiang Li, Fan Wang, Sen Lin, Qiu Shen, Xun Cao, Diming Zhang, Yuanjiang Li, Yu Li, Ying Fu, Boxin Shi, Feng Lu, Yinqiang Zheng, Robby T. Tan

This document introduces the background and the usage of the Hyperspectral City Dataset and the benchmark.

Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications

no code implementations3 May 2019 Ming Lu, Ming Cheng, Yiling Xu, ShiLiang Pu, Qiu Shen, Zhan Ma

Networked video applications, e. g., video conferencing, often suffer from poor visual quality due to unexpected network fluctuation and limited bandwidth.

Video Compression

Non-local Attention Optimized Deep Image Compression

no code implementations22 Apr 2019 Haojie Liu, Tong Chen, Peiyao Guo, Qiu Shen, Xun Cao, Yao Wang, Zhan Ma

This paper proposes a novel Non-Local Attention Optimized Deep Image Compression (NLAIC) framework, which is built on top of the popular variational auto-encoder (VAE) structure.

Image Compression MS-SSIM +1

Extreme Image Coding via Multiscale Autoencoders With Generative Adversarial Optimization

no code implementations8 Apr 2019 Chao Huang, Haojie Liu, Tong Chen, Qiu Shen, Zhan Ma

We propose a MultiScale AutoEncoder(MSAE) based extreme image compression framework to offer visually pleasing reconstruction at a very low bitrate.

Generative Adversarial Network Image Compression

Gated Context Model with Embedded Priors for Deep Image Compression

no code implementations27 Feb 2019 Haojie Liu, Tong Chen, Peiyao Guo, Qiu Shen, Zhan Ma

Besides, a field study on perceptual quality is also given via a dedicated subjective assessment, to compare the efficiency of our proposed methods and other conventional image compression methods.

Image Compression Image Reconstruction +2

Deep Image Compression via End-to-End Learning

1 code implementation5 Jun 2018 Haojie Liu, Tong Chen, Qiu Shen, Tao Yue, Zhan Ma

We present a lossy image compression method based on deep convolutional neural networks (CNNs), which outperforms the existing BPG, WebP, JPEG2000 and JPEG as measured via multi-scale structural similarity (MS-SSIM), at the same bit rate.

Image Compression MS-SSIM +3

Cannot find the paper you are looking for? You can Submit a new open access paper.