Search Results for author: Ying Tai

Found 86 papers, 38 papers with code

SSCGAN: Facial Attribute Editing via Style Skip Connections

no code implementations ECCV 2020 Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji

Each connection extracts the style feature of the latent feature maps in the encoder and then performs a residual learning based mapping function in the global information space guided by the target attributes.

Attribute Decoder +1

Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement

1 code implementation10 Nov 2024 Zhennan Chen, Yajie Li, Haofan Wang, Zhibo Chen, Zhengkai Jiang, Jun Li, Qian Wang, Jian Yang, Ying Tai

Regional prompting, or compositional generation, which enables fine-grained spatial control, has gained increasing attention for its practicality in real-world applications.

Attribute RAG +1

HybridBooth: Hybrid Prompt Inversion for Efficient Subject-Driven Generation

no code implementations10 Oct 2024 Shanyan Guan, Yanhao Ge, Ying Tai, Jian Yang, Wei Li, Mingyu You

Recent advancements in text-to-image diffusion models have shown remarkable creative capabilities with textual prompts, but generating personalized instances based on specific subjects, known as subject-driven generation, remains challenging.

Barbie: Text to Barbie-Style 3D Avatars

1 code implementation17 Aug 2024 Xiaokun Sun, Zhenyu Zhang, Ying Tai, Qian Wang, Hao Tang, Zili Yi, Jian Yang

In this paper, we propose Barbie, a novel framework for generating 3D avatars that can be dressed in diverse and high-quality Barbie-like garments and accessories.

Disentanglement Diversity

A Survey on Benchmarks of Multimodal Large Language Models

1 code implementation16 Aug 2024 Jian Li, Weiheng Lu, Hao Fei, Meng Luo, Ming Dai, Min Xia, Yizhang Jin, Zhenye Gan, Ding Qi, Chaoyou Fu, Ying Tai, Wankou Yang, Yabiao Wang, Chengjie Wang

Multimodal Large Language Models (MLLMs) are gaining increasing popularity in both academia and industry due to their remarkable performance in various applications such as visual question answering, visual perception, understanding, and reasoning.

Question Answering Survey +1

From Words to Worth: Newborn Article Impact Prediction with LLM

no code implementations7 Aug 2024 Penghai Zhao, Qinghua Xing, Kairan Dou, Jinyu Tian, Ying Tai, Jian Yang, Ming-Ming Cheng, Xiang Li

As the academic landscape expands, the challenge of efficiently identifying potentially high-impact articles among the vast number of newly published works becomes critical.

OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation

no code implementations2 Jul 2024 Kepan Nan, Rui Xie, Penghao Zhou, Tiehan Fan, Zhenheng Yang, Zhijie Chen, Xiang Li, Jian Yang, Ying Tai

Additionally, we propose a novel Multi-modal Video Diffusion Transformer (MVDiT) capable of mining both structure information from visual tokens and semantic information from text tokens.

Text-to-Video Generation Video Generation

RealTalk: Real-time and Realistic Audio-driven Face Generation with 3D Facial Prior-guided Identity Alignment Network

no code implementations26 Jun 2024 Xiaozhong Ji, Chuming Lin, Zhonggan Ding, Ying Tai, Junwei Zhu, Xiaobin Hu, Donghao Luo, Yanhao Ge, Chengjie Wang

In the second component, we design a lightweight facial identity alignment (FIA) module which includes a lip-shape control structure and a face texture reference structure.

Audio-Visual Synchronization Face Generation

MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space

no code implementations25 May 2024 Jiangwei Weng, Zhiqiang Yan, Ying Tai, Jianjun Qian, Jian Yang, Jun Li

In this paper, we introduce MambaLLIE, an implicit Retinex-aware low light enhancer featuring a global-then-local state space design.

Long-range modeling Low-Light Image Enhancement +1

Adaptive Guidance Learning for Camouflaged Object Detection

no code implementations5 May 2024 Zhennan Chen, Xuying Zhang, Tian-Zhu Xiang, Ying Tai

Then we present a hierarchical feature combination (HFC) module to deeply integrate additional cues and image features to guide camouflaged feature learning in a multi-level fusion manner. Followed by a recalibration decoder (RD), different features are further aggregated and refined for accurate object prediction.

Decoder Object +2

Anywhere: A Multi-Agent Framework for Reliable and Diverse Foreground-Conditioned Image Inpainting

no code implementations29 Apr 2024 Tianyidan Xie, Rui Ma, Qian Wang, Xiaoqian Ye, Feixuan Liu, Ying Tai, Zhenyu Zhang, Zili Yi

In the image generation module, we employ a text-guided canny-to-image generation model to create a template image based on the edge map of the foreground image and language prompts, and an image refiner to produce the outcome by blending the input foreground and the template image.

Diversity Image Inpainting +2

AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillation

1 code implementation2 Apr 2024 Rui Xie, Ying Tai, Chen Zhao, Kai Zhang, Zhenyu Zhang, Jun Zhou, Xiaoqian Ye, Qian Wang, Jian Yang

Blind super-resolution methods based on stable diffusion showcase formidable generative capabilities in reconstructing clear high-resolution images with intricate details from low-resolution inputs.

Blind Super-Resolution Super-Resolution

DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation

no code implementations26 Mar 2024 Qilin Wang, Jiangning Zhang, Chengming Xu, Weijian Cao, Ying Tai, Yue Han, Yanhao Ge, Hong Gu, Chengjie Wang, Yanwei Fu

Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and background, showing great importance in photograph.

Attribute Semantic Composition

FaceChain-ImagineID: Freely Crafting High-Fidelity Diverse Talking Faces from Disentangled Audio

1 code implementation CVPR 2024 Chao Xu, Yang Liu, Jiazheng Xing, Weida Wang, Mingze Sun, Jun Dan, Tianxin Huang, Siyuan Li, Zhi-Qi Cheng, Ying Tai, Baigui Sun

In this paper, we abstract the process of people hearing speech, extracting meaningful cues, and creating various dynamically audio-consistent talking faces, termed Listening and Imagining, into the task of high-fidelity diverse talking faces generation from a single audio.

Disentanglement

Scene Prior Filtering for Depth Super-Resolution

no code implementations21 Feb 2024 Zhengxue Wang, Zhiqiang Yan, Ming-Hsuan Yang, Jinshan Pan, Guangwei Gao, Ying Tai, Jian Yang

Specifically, we design an All-in-one Prior Propagation that computes the similarity between multi-modal scene priors, i. e., RGB, normal, semantic, and depth, to reduce the texture interference.

Depth Map Super-Resolution

Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability

no code implementations19 Feb 2024 Xuelin Qian, Yu Wang, Simian Luo, yinda zhang, Ying Tai, Zhenyu Zhang, Chengjie Wang, xiangyang xue, Bo Zhao, Tiejun Huang, Yunsheng Wu, Yanwei Fu

In this paper, we extend auto-regressive models to 3D domains, and seek a stronger ability of 3D shape generation by improving auto-regressive models at capacity and scalability simultaneously.

3D Generation 3D Shape Generation +1

A Generalist FaceX via Learning Unified Facial Representation

1 code implementation31 Dec 2023 Yue Han, Jiangning Zhang, Junwei Zhu, Xiangtai Li, Yanhao Ge, Wei Li, Chengjie Wang, Yong liu, Xiaoming Liu, Ying Tai

This work presents FaceX framework, a novel facial generalist model capable of handling diverse facial tasks simultaneously.

Facial Editing

Dynamic Frame Interpolation in Wavelet Domain

1 code implementation7 Sep 2023 Lingtong Kong, Boyuan Jiang, Donghao Luo, Wenqing Chu, Ying Tai, Chengjie Wang, Jie Yang

Video frame interpolation is an important low-level vision task, which can increase frame rate for more fluent visual experience.

Optical Flow Estimation Video Frame Interpolation

High-fidelity Generalized Emotional Talking Face Generation with Multi-modal Emotion Space Learning

no code implementations CVPR 2023 Chao Xu, Junwei Zhu, Jiangning Zhang, Yue Han, Wenqing Chu, Ying Tai, Chengjie Wang, Zhifeng Xie, Yong liu

Specifically, we supplement the emotion style in text prompts and use an Aligned Multi-modal Emotion encoder to embed the text, image, and audio emotion modality into a unified space, which inherits rich semantic prior from CLIP.

Talking Face Generation

Multimodal-driven Talking Face Generation via a Unified Diffusion-based Generator

no code implementations4 May 2023 Chao Xu, Shaoting Zhu, Junwei Zhu, Tianxin Huang, Jiangning Zhang, Ying Tai, Yong liu

More specifically, given a textured face as the source and the rendered face projected from the desired 3DMM coefficients as the target, our proposed Texture-Geometry-aware Diffusion Model decomposes the complex transfer problem into multi-conditional denoising process, where a Texture Attention-based module accurately models the correspondences between appearance and geometry cues contained in source and target conditions, and incorporate extra implicit information for high-fidelity talking face generation.

Denoising Face Swapping +1

Learning Versatile 3D Shape Generation with Improved AR Models

no code implementations26 Mar 2023 Simian Luo, Xuelin Qian, Yanwei Fu, yinda zhang, Ying Tai, Zhenyu Zhang, Chengjie Wang, xiangyang xue

Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space.

3D Shape Generation Image Generation +1

Learning Neural Proto-Face Field for Disentangled 3D Face Modeling in the Wild

no code implementations CVPR 2023 Zhenyu Zhang, Renwang Chen, Weijian Cao, Ying Tai, Chengjie Wang

To address this problem, this paper presents a novel Neural Proto-face Field (NPF) for unsupervised robust 3D face modeling.

Learning To Measure the Point Cloud Reconstruction Loss in a Representation Space

no code implementations CVPR 2023 Tianxin Huang, Zhonggan Ding, Jiangning Zhang, Ying Tai, Zhenyu Zhang, Mingang Chen, Chengjie Wang, Yong liu

Specifically, we use the contrastive constraint to help CALoss learn a representation space with shape similarity, while we introduce the adversarial strategy to help CALoss mine differences between reconstructed results and ground truths.

Point cloud reconstruction

Joint Learning Content and Degradation Aware Feature for Blind Super-Resolution

1 code implementation29 Aug 2022 Yifeng Zhou, Chuming Lin, Donghao Luo, Yong liu, Ying Tai, Chengjie Wang, Mingang Chen

Although some Unsupervised Degradation Prediction (UDP) methods are proposed to bypass this problem, the \textit{inconsistency} between degradation embedding and SR feature is still challenging.

Blind Super-Resolution Image Super-Resolution +1

SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformer

1 code implementation21 Jul 2022 Haoran Zhou, Yun Cao, Wenqing Chu, Junwei Zhu, Tong Lu, Ying Tai, Chengjie Wang

Point cloud completion has become increasingly popular among generation tasks of 3D point clouds, as it is a challenging yet indispensable problem to recover the complete shape of a 3D object from its partial observation.

Point Cloud Completion

IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation

2 code implementations CVPR 2022 Lingtong Kong, Boyuan Jiang, Donghao Luo, Wenqing Chu, Xiaoming Huang, Ying Tai, Chengjie Wang, Jie Yang

Prevailing video frame interpolation algorithms, that generate the intermediate frames from consecutive inputs, typically rely on complex model architectures with heavy parameters or large delay, hindering them from diverse real-time applications.

Decoder Optical Flow Estimation +1

FRIH: Fine-grained Region-aware Image Harmonization

no code implementations13 May 2022 Jinlong Peng, Zekun Luo, Liang Liu, Boshen Zhang, Tao Wang, Yabiao Wang, Ying Tai, Chengjie Wang, Weiyao Lin

Image harmonization aims to generate a more realistic appearance of foreground and background for a composite image.

Decoder Image Harmonization

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

High-resolution Iterative Feedback Network for Camouflaged Object Detection

1 code implementation22 Mar 2022 Xiaobin Hu, Shuo Wang, Xuebin Qin, Hang Dai, Wenqi Ren, Ying Tai, Chengjie Wang, Ling Shao

Spotting camouflaged objects that are visually assimilated into the background is tricky for both object detection algorithms and humans who are usually confused or cheated by the perfectly intrinsic similarities between the foreground objects and the background surroundings.

Object object-detection +2

CtlGAN: Few-shot Artistic Portraits Generation with Contrastive Transfer Learning

no code implementations16 Mar 2022 Yue Wang, Ran Yi, Luying Li, Ying Tai, Chengjie Wang, Lizhuang Ma

We propose a new encoder which embeds real faces into Z+ space and proposes a dual-path training strategy to better cope with the adapted decoder and eliminate the artifacts.

Decoder Image-to-Image Translation +2

ASFD: Automatic and Scalable Face Detector

no code implementations26 Jan 2022 Jian Li, Bin Zhang, Yabiao Wang, Ying Tai, Zhenyu Zhang, Chengjie Wang, Jilin Li, Xiaoming Huang, Yili Xia

Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection.

Face Detection object-detection +1

CFNet: Learning Correlation Functions for One-Stage Panoptic Segmentation

no code implementations13 Jan 2022 Yifeng Chen, Wenqing Chu, Fangfang Wang, Ying Tai, Ran Yi, Zhenye Gan, Liang Yao, Chengjie Wang, Xi Li

Recently, there is growing attention on one-stage panoptic segmentation methods which aim to segment instances and stuff jointly within a fully convolutional pipeline efficiently.

Instance Segmentation Panoptic Segmentation +1

SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

no code implementations12 Jan 2022 Jiangning Zhang, Chao Xu, Jian Li, Yue Han, Yabiao Wang, Ying Tai, Yong liu

In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-sampling operation for the target device.

Colorization Image Colorization +1

Blind Face Restoration via Integrating Face Shape and Generative Priors

no code implementations CVPR 2022 Feida Zhu, Junwei Zhu, Wenqing Chu, Xinyi Zhang, Xiaozhong Ji, Chengjie Wang, Ying Tai

Moreover, we introduce hybrid-level losses to jointly train the shape and generative priors together with other network parts such that these two priors better adapt to our blind face restoration task.

3D Reconstruction Blind Face Restoration +1

Learning To Memorize Feature Hallucination for One-Shot Image Generation

no code implementations CVPR 2022 Yu Xie, Yanwei Fu, Ying Tai, Yun Cao, Junwei Zhu, Chengjie Wang

In this paper, we propose a novel model to explicitly learn and memorize reusable features that can help hallucinate novel category images.

Hallucination Image Generation

Learning To Restore 3D Face From In-the-Wild Degraded Images

no code implementations CVPR 2022 Zhenyu Zhang, Yanhao Ge, Ying Tai, Xiaoming Huang, Chengjie Wang, Hao Tang, Dongjin Huang, Zhifeng Xie

In-the-wild 3D face modelling is a challenging problem as the predicted facial geometry and texture suffer from a lack of reliable clues or priors, when the input images are degraded.

3D Face Modelling Face Reconstruction

LCTR: On Awakening the Local Continuity of Transformer for Weakly Supervised Object Localization

no code implementations10 Dec 2021 Zhiwei Chen, Changan Wang, Yabiao Wang, Guannan Jiang, Yunhang Shen, Ying Tai, Chengjie Wang, Wei zhang, Liujuan Cao

In this paper, we propose a novel framework built upon the transformer, termed LCTR (Local Continuity TRansformer), which targets at enhancing the local perception capability of global features among long-range feature dependencies.

Inductive Bias Object +1

Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution

no code implementations NeurIPS 2021 Guangpin Tao, Xiaozhong Ji, Wenzhuo Wang, Shuo Chen, Chuming Lin, Yun Cao, Tong Lu, Donghao Luo, Ying Tai

In this paper, we propose a novel blind SR framework to super-resolve LR images degraded by arbitrary blur kernel with accurate kernel estimation in frequency domain.

Image Super-Resolution Translation

Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting

3 code implementations27 Jul 2021 Changan Wang, Qingyu Song, Boshen Zhang, Yabiao Wang, Ying Tai, Xuyi Hu, Chengjie Wang, Jilin Li, Jiayi Ma, Yang Wu

Therefore, we propose a novel count interval partition criterion called Uniform Error Partition (UEP), which always keeps the expected counting error contributions equal for all intervals to minimize the prediction risk.

Crowd Counting Quantization

Dual Reweighting Domain Generalization for Face Presentation Attack Detection

no code implementations30 Jun 2021 Shubao Liu, Ke-Yue Zhang, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Yuan Xie, Lizhuang Ma

Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios.

Domain Generalization Face Anti-Spoofing +1

Learning To Restore Hazy Video: A New Real-World Dataset and a New Method

no code implementations CVPR 2021 Xinyi Zhang, Hang Dong, Jinshan Pan, Chao Zhu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Fei Wang

On the other hand, the video dehazing algorithms, which can acquire more satisfying dehazing results by exploiting the temporal redundancy from neighborhood hazy frames, receive less attention due to the absence of the video dehazing datasets.

Image Dehazing

HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping

1 code implementation18 Jun 2021 YuHan Wang, Xu Chen, Junwei Zhu, Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Yongjian Wu, Feiyue Huang, Rongrong Ji

In this work, we propose a high fidelity face swapping method, called HifiFace, which can well preserve the face shape of the source face and generate photo-realistic results.

3D Face Reconstruction Decoder +3

Context-Aware Image Inpainting with Learned Semantic Priors

1 code implementation14 Jun 2021 Wendong Zhang, Junwei Zhu, Ying Tai, Yunbo Wang, Wenqing Chu, Bingbing Ni, Chengjie Wang, Xiaokang Yang

Based on the semantic priors, we further propose a context-aware image inpainting model, which adaptively integrates global semantics and local features in a unified image generator.

Image Inpainting Knowledge Distillation

Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model

1 code implementation NeurIPS 2021 Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang, Ying Tai, Shuo Chen, Chengjie Wang, Feiyue Huang, Yong liu

Inspired by biological evolution, we explain the rationality of Vision Transformer by analogy with the proven practical Evolutionary Algorithm (EA) and derive that both of them have consistent mathematical representation.

Image Retrieval Retrieval

SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking

no code implementations24 May 2021 Jinlong Peng, Zhengkai Jiang, Yueyang Gu, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Weiyao Lin

In addition, we add a localization branch to predict the localization accuracy, so that it can work as the replacement of the regression assistance link during inference.

Classification Object +2

Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing

no code implementations6 May 2021 Zhihong Chen, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Feiyue Huang, Xinyu Jin

Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios.

Domain Generalization Face Anti-Spoofing +2

Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification

1 code implementation CVPR 2020 Yichao Yan, Jie Qin1, Jiaxin Chen, Li Liu, Fan Zhu, Ying Tai, Ling Shao

In each hypergraph, different temporal granularities are captured by hyperedges that connect a set of graph nodes (i. e., part-based features) across different temporal ranges.

Video-Based Person Re-Identification

Learning Comprehensive Motion Representation for Action Recognition

no code implementations23 Mar 2021 Mingyu Wu, Boyuan Jiang, Donghao Luo, Junchi Yan, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Xiaokang Yang

For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame.

Action Recognition

Uniformity in Heterogeneity: Diving Deep Into Count Interval Partition for Crowd Counting

1 code implementation ICCV 2021 Changan Wang, Qingyu Song, Boshen Zhang, Yabiao Wang, Ying Tai, Xuyi Hu, Chengjie Wang, Jilin Li, Jiayi Ma, Yang Wu

Therefore, we propose a novel count interval partition criterion called Uniform Error Partition (UEP), which always keeps the expected counting error contributions equal for all intervals to minimize the prediction risk.

Crowd Counting Quantization

Frequency Consistent Adaptation for Real World Super Resolution

no code implementations18 Dec 2020 Xiaozhong Ji, Guangpin Tao, Yun Cao, Ying Tai, Tong Lu, Chengjie Wang, Jilin Li, Feiyue Huang

From this point of view, we design a novel Frequency Consistent Adaptation (FCA) that ensures the frequency domain consistency when applying existing SR methods to the real scene.

Super-Resolution

They are Not Completely Useless: Towards Recycling Transferable Unlabeled Data for Class-Mismatched Semi-Supervised Learning

no code implementations27 Nov 2020 Zhuo Huang, Ying Tai, Chengjie Wang, Jian Yang, Chen Gong

Semi-Supervised Learning (SSL) with mismatched classes deals with the problem that the classes-of-interests in the limited labeled data is only a subset of the classes in massive unlabeled data.

Domain Adaptation

Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

1 code implementation ECCV 2020 Jinlong Peng, Changan Wang, Fangbin Wan, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yanwei Fu

Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or have two of the three subtasks integrated to form a partially end-to-end solution.

Multiple Object Tracking Object +3

Temporal Distinct Representation Learning for Action Recognition

no code implementations ECCV 2020 Junwu Weng, Donghao Luo, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Xudong Jiang, Junsong Yuan

Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos.

Action Recognition Diversity +1

Collaborative Learning for Faster StyleGAN Embedding

no code implementations3 Jul 2020 Shanyan Guan, Ying Tai, Bingbing Ni, Feida Zhu, Feiyue Huang, Xiaokang Yang

The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator.

CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

2 code implementations CVPR 2020 Yuge Huang, YuHan Wang, Ying Tai, Xiaoming Liu, Pengcheng Shen, Shaoxin Li, Jilin Li, Feiyue Huang

As an emerging topic in face recognition, designing margin-based loss functions can increase the feature margin between different classes for enhanced discriminability.

Ranked #13 on Face Verification on IJB-C (TAR @ FAR=1e-4 metric)

Face Recognition Face Verification

ASFD: Automatic and Scalable Face Detector

no code implementations25 Mar 2020 Bin Zhang, Jian Li, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yili Xia, Wenjiang Pei, Rongrong Ji

In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design.

Neural Architecture Search

Improving Face Recognition from Hard Samples via Distribution Distillation Loss

2 code implementations ECCV 2020 Yuge Huang, Pengcheng Shen, Ying Tai, Shaoxin Li, Xiaoming Liu, Jilin Li, Feiyue Huang, Rongrong Ji

To improve the performance on those hard samples for general tasks, we propose a novel Distribution Distillation Loss to narrow the performance gap between easy and hard samples, which is a simple, effective and generic for various types of facial variations.

Face Recognition

FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization

no code implementations26 Nov 2019 Xi Yin, Ying Tai, Yuge Huang, Xiaoming Liu

FAN can leverage both paired and unpaired data as we disentangle the features into identity and non-identity components and adapt the distribution of the identity features, which breaks the limit of current face super-resolution methods.

Face Recognition Super-Resolution

TEINet: Towards an Efficient Architecture for Video Recognition

no code implementations21 Nov 2019 Zhao-Yang Liu, Donghao Luo, Yabiao Wang, Li-Min Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Tong Lu

To relieve this problem, we propose an efficient temporal module, termed as Temporal Enhancement-and-Interaction (TEI Module), which could be plugged into the existing 2D CNNs (denoted by TEINet).

Action Recognition Video Recognition

Fast Learning of Temporal Action Proposal via Dense Boundary Generator

3 code implementations11 Nov 2019 Chuming Lin, Jian Li, Yabiao Wang, Ying Tai, Donghao Luo, Zhipeng Cui, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji

In this paper, we propose an efficient and unified framework to generate temporal action proposals named Dense Boundary Generator (DBG), which draws inspiration from boundary-sensitive methods and implements boundary classification and action completeness regression for densely distributed proposals.

General Classification Optical Flow Estimation +2

Anti-Confusing: Region-Aware Network for Human Pose Estimation

no code implementations3 May 2019 Xuan Cao, Yanhao Ge, Ying Tai, Wei zhang, Jian Li, Chengjie Wang, Jilin Li, Feiyue Huang

In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric appearance, for human pose estimation.

Data Augmentation Pose Estimation

Aurora Guard: Real-Time Face Anti-Spoofing via Light Reflection

no code implementations27 Feb 2019 Yao Liu, Ying Tai, Jilin Li, Shouhong Ding, Chengjie Wang, Feiyue Huang, Dongyang Li, Wenshuai Qi, Rongrong Ji

In this paper, we propose a light reflection based face anti-spoofing method named Aurora Guard (AG), which is fast, simple yet effective that has already been deployed in real-world systems serving for millions of users.

Face Anti-Spoofing General Classification

Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos

1 code implementation1 Nov 2018 Ying Tai, Yicong Liang, Xiaoming Liu, Lei Duan, Jilin Li, Chengjie Wang, Feiyue Huang, Yu Chen

In recent years, heatmap regression based models have shown their effectiveness in face alignment and pose estimation.

Face Alignment Pose Estimation +3

DSFD: Dual Shot Face Detector

4 code implementations CVPR 2019 Jian Li, Yabiao Wang, Changan Wang, Ying Tai, Jianjun Qian, Jian Yang, Chengjie Wang, Jilin Li, Feiyue Huang

In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progressive loss design and anchor assign based data augmentation, respectively.

Data Augmentation Occluded Face Detection

Person Search via A Mask-Guided Two-Stream CNN Model

no code implementations ECCV 2018 Di Chen, Shanshan Zhang, Wanli Ouyang, Jian Yang, Ying Tai

In this work, we tackle the problem of person search, which is a challenging task consisted of pedestrian detection and person re-identification~(re-ID).

Pedestrian Detection Person Re-Identification +2

FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

4 code implementations CVPR 2018 Yu Chen, Ying Tai, Xiaoming Liu, Chunhua Shen, Jian Yang

We present a novel deep end-to-end trainable Face Super-Resolution Network (FSRNet), which makes full use of the geometry prior, i. e., facial landmark heatmaps and parsing maps, to super-resolve very low-resolution (LR) face images without well-aligned requirement.

Decoder Face Alignment +2

Image Super-Resolution via Deep Recursive Residual Network

1 code implementation CVPR 2017 Ying Tai, Jian Yang, Xiaoming Liu

Specifically, residual learning is adopted, both in global and local manners, to mitigate the difficulty of training very deep networks; recursive learning is used to control the model parameters while increasing the depth.

Image Super-Resolution Video Super-Resolution

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