Search Results for author: Wenhan Luo

Found 73 papers, 35 papers with code

Beyond Monocular Deraining: Stereo Image Deraining via Semantic Understanding

no code implementations ECCV 2020 Kaihao Zhang, Wenhan Luo, Wenqi Ren, Jingwen Wang Fang Zhao, Lin Ma , Hongdong Li

Moreover, even for single image based monocular deraining, many current methods fail to complete the task satisfactorily because they mostly rely on per pixel loss functions and ignoring semantic information.

Benchmarking Rain Removal +1

M-LRM: Multi-view Large Reconstruction Model

no code implementations11 Jun 2024 Mengfei Li, Xiaoxiao Long, Yixun Liang, Weiyu Li, YuAn Liu, Peng Li, Xiaowei Chi, Xingqun Qi, Wei Xue, Wenhan Luo, Qifeng Liu, Yike Guo

Despite recent advancements in the Large Reconstruction Model (LRM) demonstrating impressive results, when extending its input from single image to multiple images, it exhibits inefficiencies, subpar geometric and texture quality, as well as slower convergence speed than expected.

3D Reconstruction

Follow-Your-Pose v2: Multiple-Condition Guided Character Image Animation for Stable Pose Control

no code implementations5 Jun 2024 Jingyun Xue, Hongfa Wang, Qi Tian, Yue Ma, Andong Wang, Zhiyuan Zhao, Shaobo Min, Wenzhe Zhao, Kaihao Zhang, Heung-Yeung Shum, Wei Liu, Mengyang Liu, Wenhan Luo

While existing character image animation methods using pose sequences and reference images have shown promising performance, they tend to struggle with incoherent animation in complex scenarios, such as multiple character animation and body occlusion.

Image Animation Video Generation

Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention

no code implementations19 May 2024 Peng Li, YuAn Liu, Xiaoxiao Long, Feihu Zhang, Cheng Lin, Mengfei Li, Xingqun Qi, Shanghang Zhang, Wenhan Luo, Ping Tan, Wenping Wang, Qifeng Liu, Yike Guo

Specifically, these methods assume that the input images should comply with a predefined camera type, e. g. a perspective camera with a fixed focal length, leading to distorted shapes when the assumption fails.

Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts

1 code implementation18 May 2024 Yunxin Li, Shenyuan Jiang, Baotian Hu, Longyue Wang, Wanqi Zhong, Wenhan Luo, Lin Ma, Min Zhang

Although the Mixture of Experts (MoE) architecture has been employed to efficiently scale large language and image-text models, these efforts typically involve fewer experts and limited modalities.

Visual Question Answering

Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost

no code implementations9 May 2024 Yuan Gao, Weizhong Zhang, Wenhan Luo, Lin Ma, Jin-Gang Yu, Gui-Song Xia, Jiayi Ma

We aim at exploiting additional auxiliary labels from an independent (auxiliary) task to boost the primary task performance which we focus on, while preserving a single task inference cost of the primary task.

Auxiliary Learning Neural Architecture Search

Context-Aware Integration of Language and Visual References for Natural Language Tracking

no code implementations CVPR 2024 Yanyan Shao, Shuting He, Qi Ye, Yuchao Feng, Wenhan Luo, Jiming Chen

Tracking by natural language specification (TNL) aims to consistently localize a target in a video sequence given a linguistic description in the initial frame.

OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

1 code implementation16 Mar 2024 Zhe Kong, Yong Zhang, Tianyu Yang, Tao Wang, Kaihao Zhang, Bizhu Wu, GuanYing Chen, Wei Liu, Wenhan Luo

We also observe that the initiation denoising timestep for noise blending is the key to identity preservation and layout.

Denoising Text-to-Image Generation

AS-FIBA: Adaptive Selective Frequency-Injection for Backdoor Attack on Deep Face Restoration

no code implementations11 Mar 2024 Zhenbo Song, Wenhao Gao, Kaihao Zhang, Wenhan Luo, Zhaoxin Fan, Jianfeng Lu

Extensive experiments demonstrate the efficacy of the degradation objective on state-of-the-art face restoration models.

Backdoor Attack

Segmentation Guided Sparse Transformer for Under-Display Camera Image Restoration

no code implementations9 Mar 2024 Jingyun Xue, Tao Wang, Jun Wang, Kaihao Zhang, Wenhan Luo, Wenqi Ren, Zikun Liu, Hyunhee Park, Xiaochun Cao

Specifically, we utilize sparse self-attention to filter out redundant information and noise, directing the model's attention to focus on the features more relevant to the degraded regions in need of reconstruction.

Image Restoration Instance Segmentation +1

SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt Denoising

1 code implementation7 Mar 2024 Tao Zhou, Wenhan Luo, Qi Ye, Zhiguo Shi, Jiming Chen

Recently, promptable segmentation models, such as the Segment Anything Model (SAM), have demonstrated robust zero-shot generalization capabilities on static images.

Denoising Instance Segmentation +4

Adversarial Purification and Fine-tuning for Robust UDC Image Restoration

no code implementations21 Feb 2024 Zhenbo Song, Zhenyuan Zhang, Kaihao Zhang, Wenhan Luo, Zhaoxin Fan, Jianfeng Lu

This study delves into the enhancement of Under-Display Camera (UDC) image restoration models, focusing on their robustness against adversarial attacks.

Adversarial Purification Image Restoration

A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation

1 code implementation21 Feb 2024 Yunxin Li, Baotian Hu, Wenhan Luo, Lin Ma, Yuxin Ding, Min Zhang

For this setting, previous methods utilize visual and textual encoders to encode the image and keywords and employ a language model-based decoder to generate the product description.

In-Context Learning Language Modelling +2

PromptRR: Diffusion Models as Prompt Generators for Single Image Reflection Removal

1 code implementation4 Feb 2024 Tao Wang, Wanglong Lu, Kaihao Zhang, Wenhan Luo, Tae-Kyun Kim, Tong Lu, Hongdong Li, Ming-Hsuan Yang

For the prompt generation, we first propose a prompt pre-training strategy to train a frequency prompt encoder that encodes the ground-truth image into LF and HF prompts.

Reflection Removal

Dual Teacher Knowledge Distillation with Domain Alignment for Face Anti-spoofing

no code implementations2 Jan 2024 Zhe Kong, Wentian Zhang, Tao Wang, Kaihao Zhang, Yuexiang Li, Xiaoying Tang, Wenhan Luo

In this paper, we propose a domain adversarial attack (DAA) method to mitigate the training instability problem by adding perturbations to the input images, which makes them indistinguishable across domains and enables domain alignment.

Adversarial Attack Face Anti-Spoofing +2

Towards Real-World Blind Face Restoration with Generative Diffusion Prior

1 code implementation25 Dec 2023 Xiaoxu Chen, Jingfan Tan, Tao Wang, Kaihao Zhang, Wenhan Luo, Xiaochun Cao

We propose BFRffusion which is thoughtfully designed to effectively extract features from low-quality face images and could restore realistic and faithful facial details with the generative prior of the pretrained Stable Diffusion.

Blind Face Restoration Privacy Preserving

Weakly-Supervised Emotion Transition Learning for Diverse 3D Co-speech Gesture Generation

no code implementations CVPR 2024 Xingqun Qi, Jiahao Pan, Peng Li, Ruibin Yuan, Xiaowei Chi, Mengfei Li, Wenhan Luo, Wei Xue, Shanghang Zhang, Qifeng Liu, Yike Guo

In addition, the lack of large-scale available datasets with emotional transition speech and corresponding 3D human gestures also limits the addressing of this task.

Audio inpainting Gesture Generation

M$^{2}$Chat: Empowering VLM for Multimodal LLM Interleaved Text-Image Generation

1 code implementation29 Nov 2023 Xiaowei Chi, Rongyu Zhang, Zhengkai Jiang, Yijiang Liu, Yatian Wang, Xingqun Qi, Wenhan Luo, Peng Gao, Shanghang Zhang, Qifeng Liu, Yike Guo

Moreover, to further enhance the effectiveness of $M^{3}Adapter$ while preserving the coherence of semantic context comprehension, we introduce a two-stage $M^{3}FT$ fine-tuning strategy.

Image Generation Language Modelling +1

Deep Video Restoration for Under-Display Camera

no code implementations9 Sep 2023 Xuanxi Chen, Tao Wang, Ziqian Shao, Kaihao Zhang, Wenhan Luo, Tong Lu, Zikun Liu, Tae-Kyun Kim, Hongdong Li

With the pipeline, we build the first large-scale UDC video restoration dataset called PexelsUDC, which includes two subsets named PexelsUDC-T and PexelsUDC-P corresponding to different displays for UDC.

Video Restoration

MB-TaylorFormer: Multi-branch Efficient Transformer Expanded by Taylor Formula for Image Dehazing

1 code implementation ICCV 2023 Yuwei Qiu, Kaihao Zhang, Chenxi Wang, Wenhan Luo, Hongdong Li, Zhi Jin

To address this issue, we propose a new Transformer variant, which applies the Taylor expansion to approximate the softmax-attention and achieves linear computational complexity.

Image Dehazing

InterTracker: Discovering and Tracking General Objects Interacting with Hands in the Wild

no code implementations6 Aug 2023 Yanyan Shao, Qi Ye, Wenhan Luo, Kaihao Zhang, Jiming Chen

Understanding human interaction with objects is an important research topic for embodied Artificial Intelligence and identifying the objects that humans are interacting with is a primary problem for interaction understanding.

Object Object Tracking

LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement

1 code implementation27 Jul 2023 Tao Wang, Kaihao Zhang, Ziqian Shao, Wenhan Luo, Bjorn Stenger, Tae-Kyun Kim, Wei Liu, Hongdong Li

In this paper, we address this limitation by proposing a degradation-aware learning scheme for LLIE using diffusion models, which effectively integrates degradation and image priors into the diffusion process, resulting in improved image enhancement.

Image Generation Low-Light Image Enhancement

HTNet for micro-expression recognition

1 code implementation27 Jul 2023 Zhifeng Wang, Kaihao Zhang, Wenhan Luo, Ramesh Sankaranarayana

The transformer layer is used to focus on representing local minor muscle movement with local self-attention in each area.

 Ranked #1 on Micro-Expression Recognition on CASME II (using extra training data)

Facial Emotion Recognition Micro Expression Recognition +1

PRIOR: Prototype Representation Joint Learning from Medical Images and Reports

1 code implementation ICCV 2023 Pujin Cheng, Li Lin, Junyan Lyu, Yijin Huang, Wenhan Luo, Xiaoying Tang

In this paper, we present a prototype representation learning framework incorporating both global and local alignment between medical images and reports.

Contrastive Learning Image-to-Text Retrieval +8

DREAM: Domain-free Reverse Engineering Attributes of Black-box Model

no code implementations20 Jul 2023 Rongqing Li, Jiaqi Yu, Changsheng Li, Wenhan Luo, Ye Yuan, Guoren Wang

There is a crucial limitation: these works assume the dataset used for training the target model to be known beforehand and leverage this dataset for model attribute attack.


Learning Enhancement From Degradation: A Diffusion Model For Fundus Image Enhancement

1 code implementation8 Mar 2023 Puijin Cheng, Li Lin, Yijin Huang, Huaqing He, Wenhan Luo, Xiaoying Tang

In this paper, we introduce a novel diffusion model based framework, named Learning Enhancement from Degradation (LED), for enhancing fundus images.

Image Enhancement

Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method

1 code implementation22 Dec 2022 Tao Wang, Kaihao Zhang, Tianrun Shen, Wenhan Luo, Bjorn Stenger, Tong Lu

In this paper, we consider the task of low-light image enhancement (LLIE) and introduce a large-scale database consisting of images at 4K and 8K resolution.

4k 8k +3

ADTR: Anomaly Detection Transformer with Feature Reconstruction

no code implementations5 Sep 2022 Zhiyuan You, Kai Yang, Wenhan Luo, Lei Cui, Yu Zheng, Xinyi Le

Second, CNN tends to reconstruct both normal samples and anomalies well, making them still hard to distinguish.

Anomaly Detection

Multi-Prior Learning via Neural Architecture Search for Blind Face Restoration

1 code implementation28 Jun 2022 Yanjiang Yu, Puyang Zhang, Kaihao Zhang, Wenhan Luo, Changsheng Li, Ye Yuan, Guoren Wang

To this end, we propose a Face Restoration Searching Network (FRSNet) to adaptively search the suitable feature extraction architecture within our specified search space, which can directly contribute to the restoration quality.

Blind Face Restoration Neural Architecture Search

Blind Face Restoration: Benchmark Datasets and a Baseline Model

2 code implementations8 Jun 2022 Puyang Zhang, Kaihao Zhang, Wenhan Luo, Changsheng Li, Guoren Wang

To address this problem, we first synthesize two blind face restoration benchmark datasets called EDFace-Celeb-1M (BFR128) and EDFace-Celeb-150K (BFR512).

Blind Face Restoration

Aesthetic Text Logo Synthesis via Content-aware Layout Inferring

1 code implementation CVPR 2022 Yizhi Wang, Guo Pu, Wenhan Luo, Yexin Wang, Pengfei Xiong, Hongwen Kang, Zhouhui Lian

To train and evaluate our approach, we construct a dataset named as TextLogo3K, consisting of about 3, 500 text logo images and their pixel-level annotations.

Layout Design

Deep Image Deblurring: A Survey

no code implementations26 Jan 2022 Kaihao Zhang, Wenqi Ren, Wenhan Luo, Wei-Sheng Lai, Bjorn Stenger, Ming-Hsuan Yang, Hongdong Li

Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image.

Deblurring Image Deblurring

Few-shot Object Counting with Similarity-Aware Feature Enhancement

1 code implementation22 Jan 2022 Zhiyuan You, Kai Yang, Wenhan Luo, Xin Lu, Lei Cui, Xinyi Le

This work studies the problem of few-shot object counting, which counts the number of exemplar objects (i. e., described by one or several support images) occurring in the query image.

Crowd Counting Object Counting

MC-Blur: A Comprehensive Benchmark for Image Deblurring

2 code implementations1 Dec 2021 Kaihao Zhang, Tao Wang, Wenhan Luo, Boheng Chen, Wenqi Ren, Bjorn Stenger, Wei Liu, Hongdong Li, Ming-Hsuan Yang

Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios.

Benchmarking Deblurring +1

Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-Mixing

1 code implementation9 Sep 2021 Zhe Kong, Wentian Zhang, Feng Liu, Wenhan Luo, Haozhe Liu, Linlin Shen, Raghavendra Ramachandra

Even though there are numerous Presentation Attack Detection (PAD) techniques based on both deep learning and hand-crafted features, the generalization of PAD for unknown PAI is still a challenging problem.

Self-Supervised Learning

Towards Distraction-Robust Active Visual Tracking

no code implementations18 Jun 2021 Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang

In active visual tracking, it is notoriously difficult when distracting objects appear, as distractors often mislead the tracker by occluding the target or bringing a confusing appearance.

Visual Tracking

T-Net: Deep Stacked Scale-Iteration Network for Image Dehazing

no code implementations5 Jun 2021 Lirong Zheng, Yanshan Li, Kaihao Zhang, Wenhan Luo

In order to reduce network parameters, the intra-stage recursive computation of ResNet is adopted in our Stack T-Net.

Image Dehazing

Beyond Monocular Deraining: Parallel Stereo Deraining Network Via Semantic Prior

no code implementations9 May 2021 Kaihao Zhang, Wenhan Luo, Yanjiang Yu, Wenqi Ren, Fang Zhao, Changsheng Li, Lin Ma, Wei Liu, Hongdong Li

We first use a coarse deraining network to reduce the rain streaks on the input images, and then adopt a pre-trained semantic segmentation network to extract semantic features from the coarse derained image.

Benchmarking Rain Removal +1

Enhanced Spatio-Temporal Interaction Learning for Video Deraining: A Faster and Better Framework

1 code implementation23 Mar 2021 Kaihao Zhang, Dongxu Li, Wenhan Luo, Wenqi Ren, Wei Liu

Video deraining is an important task in computer vision as the unwanted rain hampers the visibility of videos and deteriorates the robustness of most outdoor vision systems.

Rain Removal

Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priors

no code implementations21 Mar 2021 Kaihao Zhang, Rongqing Li, Yanjiang Yu, Wenhan Luo, Changsheng Li, Hongdong Li

Images captured in snowy days suffer from noticeable degradation of scene visibility, which degenerates the performance of current vision-based intelligent systems.

Image Restoration Snow Removal

Dual Attention-in-Attention Model for Joint Rain Streak and Raindrop Removal

no code implementations12 Mar 2021 Kaihao Zhang, Dongxu Li, Wenhan Luo, Wenqi Ren

In addition, to further refine the result, a Differential-driven Dual Attention-in-Attention Model (D-DAiAM) is proposed with a "heavy-to-light" scheme to remove rain via addressing the unsatisfying deraining regions.

Rain Removal

Benchmarking Ultra-High-Definition Image Super-Resolution

no code implementations ICCV 2021 Kaihao Zhang, Dongxu Li, Wenhan Luo, Wenqi Ren, Bjorn Stenger, Wei Liu, Hongdong Li, Ming-Hsuan Yang

Increasingly, modern mobile devices allow capturing images at Ultra-High-Definition (UHD) resolution, which includes 4K and 8K images.

4k 8k +3

Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis

2 code implementations18 Nov 2020 Wen Liu, Zhixin Piao, Zhi Tu, Wenhan Luo, Lin Ma, Shenghua Gao

Also, we build a new dataset, namely iPER dataset, for the evaluation of human motion imitation, appearance transfer, and novel view synthesis.

Denoising Image Generation +1

Deblurring by Realistic Blurring

1 code implementation CVPR 2020 Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Bjorn Stenger, Wei Liu, Hongdong Li

To address this problem, we propose a new method which combines two GAN models, i. e., a learning-to-Blur GAN (BGAN) and learning-to-DeBlur GAN (DBGAN), in order to learn a better model for image deblurring by primarily learning how to blur images.

Deblurring Image Deblurring

Look Closer to Ground Better: Weakly-Supervised Temporal Grounding of Sentence in Video

no code implementations25 Jan 2020 Zhenfang Chen, Lin Ma, Wenhan Luo, Peng Tang, Kwan-Yee K. Wong

In this paper, we study the problem of weakly-supervised temporal grounding of sentence in video.


Fine-grained Image-to-Image Transformation towards Visual Recognition

no code implementations CVPR 2020 Wei Xiong, Yutong He, Yixuan Zhang, Wenhan Luo, Lin Ma, Jiebo Luo

In this paper, we aim at transforming an image with a fine-grained category to synthesize new images that preserve the identity of the input image, which can thereby benefit the subsequent fine-grained image recognition and few-shot learning tasks.

Few-Shot Learning Fine-Grained Image Recognition

Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling

no code implementations18 Dec 2019 Tianrui Liu, Wenhan Luo, Lin Ma, Jun-Jie Huang, Tania Stathaki, Tianhong Dai

Ablation studies have validated the effectiveness of both the proposed gated multi-layer feature extraction sub-network and the deformable occlusion handling sub-network.

Occlusion Handling Pedestrian Detection

Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis

2 code implementations ICCV 2019 Wen Liu, Zhixin Piao, Jie Min, Wenhan Luo, Lin Ma, Shenghua Gao

In this paper, we propose to use a 3D body mesh recovery module to disentangle the pose and shape, which can not only model the joint location and rotation but also characterize the personalized body shape.

Denoising Novel View Synthesis

Weakly-Supervised Spatio-Temporally Grounding Natural Sentence in Video

1 code implementation ACL 2019 Zhenfang Chen, Lin Ma, Wenhan Luo, Kwan-Yee K. Wong

In this paper, we address a novel task, namely weakly-supervised spatio-temporally grounding natural sentence in video.

object-detection Sentence +1

AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking

no code implementations ICLR 2019 Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang

In AD-VAT, both the tracker and the target are approximated by end-to-end neural networks, and are trained via RL in a dueling/competitive manner: i. e., the tracker intends to lockup the target, while the target tries to escape from the tracker.

Learning to Compose Dynamic Tree Structures for Visual Contexts

6 code implementations CVPR 2019 Kaihua Tang, Hanwang Zhang, Baoyuan Wu, Wenhan Luo, Wei Liu

We propose to compose dynamic tree structures that place the objects in an image into a visual context, helping visual reasoning tasks such as scene graph generation and visual Q&A.

Graph Generation Panoptic Scene Graph Generation +2

Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance

1 code implementation4 Nov 2018 Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng

To address the training difficulty, we propose a training algorithm using a tighter approximation to the derivative of the sign function, a magnitude-aware gradient for weight updating, a better initialization method, and a two-step scheme for training a deep network.

Depth Estimation

End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning

no code implementations10 Aug 2018 Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang

We further propose an environment augmentation technique and a customized reward function, which are crucial for successful training.

Object Object Tracking +1

Adversarial Spatio-Temporal Learning for Video Deblurring

1 code implementation28 Mar 2018 Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Wei Liu, Hongdong Li

To tackle the second challenge, we leverage the developed DBLRNet as a generator in the GAN (generative adversarial network) architecture, and employ a content loss in addition to an adversarial loss for efficient adversarial training.

Deblurring Generative Adversarial Network

Real-Time Neural Style Transfer for Videos

no code implementations CVPR 2017 Hao-Zhi Huang, Hao Wang, Wenhan Luo, Lin Ma, Wenhao Jiang, Xiaolong Zhu, Zhifeng Li, Wei Liu

More specifically, a hybrid loss is proposed to capitalize on the content information of input frames, the style information of a given style image, and the temporal information of consecutive frames.

Style Transfer Video Style Transfer

End-to-end Active Object Tracking via Reinforcement Learning

no code implementations ICML 2018 Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang

We study active object tracking, where a tracker takes as input the visual observation (i. e., frame sequence) and produces the camera control signal (e. g., move forward, turn left, etc.).

Object Object Tracking +2

Multiple Object Tracking: A Literature Review

no code implementations26 Sep 2014 Wenhan Luo, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Tae-Kyun Kim

We inspect the recent advances in various aspects and propose some interesting directions for future research.

Multiple Object Tracking Object

Bi-label Propagation for Generic Multiple Object Tracking

no code implementations CVPR 2014 Wenhan Luo, Tae-Kyun Kim, Bjorn Stenger, Xiaowei Zhao, Roberto Cipolla

In this paper, we propose a label propagation framework to handle the multiple object tracking (MOT) problem for a generic object type (cf.

Multiple Object Tracking Object

Unified Face Analysis by Iterative Multi-Output Random Forests

no code implementations CVPR 2014 Xiaowei Zhao, Tae-Kyun Kim, Wenhan Luo

In this paper, we present a unified method for joint face image analysis, i. e., simultaneously estimating head pose, facial expression and landmark positions in real-world face images.

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