Search Results for author: Yuqian Zhou

Found 29 papers, 19 papers with code

Image as Set of Points

2 code implementations2 Mar 2023 Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu

Context clusters (CoCs) view an image as a set of unorganized points and extract features via simplified clustering algorithm.


Keys to Better Image Inpainting: Structure and Texture Go Hand in Hand

1 code implementation5 Aug 2022 Jitesh Jain, Yuqian Zhou, Ning Yu, Humphrey Shi

We claim that the performance of inpainting algorithms can be better judged by the generated structures and textures.

Image Inpainting Texture Synthesis

Perceptual Artifacts Localization for Inpainting

1 code implementation5 Aug 2022 Lingzhi Zhang, Yuqian Zhou, Connelly Barnes, Sohrab Amirghodsi, Zhe Lin, Eli Shechtman, Jianbo Shi

Inspired by this workflow, we propose a new learning task of automatic segmentation of inpainting perceptual artifacts, and apply the model for inpainting model evaluation and iterative refinement.

Image Inpainting

Towards Layer-wise Image Vectorization

1 code implementation CVPR 2022 Xu Ma, Yuqian Zhou, Xingqian Xu, Bin Sun, Valerii Filev, Nikita Orlov, Yun Fu, Humphrey Shi

Image rasterization is a mature technique in computer graphics, while image vectorization, the reverse path of rasterization, remains a major challenge.

GeoFill: Reference-Based Image Inpainting with Better Geometric Understanding

no code implementations20 Jan 2022 Yunhan Zhao, Connelly Barnes, Yuqian Zhou, Eli Shechtman, Sohrab Amirghodsi, Charless Fowlkes

Our approach achieves state-of-the-art performance on both RealEstate10K and MannequinChallenge dataset with large baselines, complex geometry and extreme camera motions.

Image Inpainting Monocular Depth Estimation

Image Super-Resolution With Non-Local Sparse Attention

1 code implementation CVPR 2021 Yiqun Mei, Yuchen Fan, Yuqian Zhou

NLSA is designed to retain long-range modeling capability from NL operation while enjoying robustness and high-efficiency of sparse representation.

Image Super-Resolution Long-range modeling

Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels

1 code implementation5 Mar 2021 Yuqian Zhou, Hanchao Yu, Humphrey Shi

Retinal vessel segmentation from retinal images is an essential task for developing the computer-aided diagnosis system for retinal diseases.

Retinal Vessel Segmentation Segmentation

Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining

3 code implementations CVPR 2020 Yiqun Mei, Yuchen Fan, Yuqian Zhou, Lichao Huang, Thomas S. Huang, Humphrey Shi

By combining the new CS-NL prior with local and in-scale non-local priors in a powerful recurrent fusion cell, we can find more cross-scale feature correlations within a single low-resolution (LR) image.

Image Super-Resolution

Pyramid Attention Networks for Image Restoration

2 code implementations28 Apr 2020 Yiqun Mei, Yuchen Fan, Yulun Zhang, Jiahui Yu, Yuqian Zhou, Ding Liu, Yun Fu, Thomas S. Huang, Humphrey Shi

Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different locations and scales.

Demosaicking Image Denoising +1

FLNet: Landmark Driven Fetching and Learning Network for Faithful Talking Facial Animation Synthesis

no code implementations21 Nov 2019 Kuangxiao Gu, Yuqian Zhou, Thomas Huang

In this paper, We present a landmark driven two-stream network to generate faithful talking facial animation, in which more facial details are created, preserved and transferred from multiple source images instead of a single one.

Face Generation

When AWGN-based Denoiser Meets Real Noises

2 code implementations6 Apr 2019 Yuqian Zhou, Jianbo Jiao, Haibin Huang, Yang Wang, Jue Wang, Honghui Shi, Thomas Huang

In this paper, we propose a novel approach to boost the performance of a real image denoiser which is trained only with synthetic pixel-independent noise data dominated by AWGN.


Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification

1 code implementation ICCV 2019 Yang Fu, Yunchao Wei, Guanshuo Wang, Yuqian Zhou, Honghui Shi, Thomas Huang

Upon our SSG, we further introduce a clustering-guided semisupervised approach named SSG ++ to conduct the one-shot domain adaption in an open set setting (i. e. the number of independent identities from the target domain is unknown).

Clustering One-Shot Learning +2

Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features

2 code implementations2 May 2018 Didan Deng, Yuqian Zhou, Jimin Pi, Bertram E. Shi

The integration of information across multiple modalities and across time is a promising way to enhance the emotion recognition performance of affective systems.

Emotion Recognition

Unsupervised Representation Adversarial Learning Network: from Reconstruction to Generation

1 code implementation19 Apr 2018 Yuqian Zhou, Kuangxiao Gu, Thomas Huang

The newly proposed RepGAN is tested on MNIST, fashionMNIST, CelebA, and SVHN datasets to perform unsupervised classification, generation and reconstruction tasks.

Clustering General Classification

Survey of Face Detection on Low-quality Images

no code implementations19 Apr 2018 Yuqian Zhou, Ding Liu, Thomas Huang

However, previous proposed models are mostly trained and tested on good-quality images which are not always the case for practical applications like surveillance systems.

Face Detection Robust Design

Horizontal Pyramid Matching for Person Re-identification

1 code implementation14 Apr 2018 Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, Thomas Huang

Despite the remarkable recent progress, person re-identification (Re-ID) approaches are still suffering from the failure cases where the discriminative body parts are missing.

Person Re-Identification

Photorealistic Facial Expression Synthesis by the Conditional Difference Adversarial Autoencoder

no code implementations30 Aug 2017 Yuqian Zhou, Bertram Emil Shi

It handles the problem of disambiguating changes due to identity and changes due to facial expression by learning to generate the difference between low-level features of images of the same person but with different facial expressions.

Data Augmentation Emotion Recognition +1

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