Search Results for author: Zhanpeng Zhang

Found 9 papers, 2 papers with code

Learning Social Relation Traits from Face Images

no code implementations ICCV 2015 Zhanpeng Zhang, Ping Luo, Chen Change Loy, Xiaoou Tang

Social relation defines the association, e. g, warm, friendliness, and dominance, between two or more people.

Attribute Relation

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

42 code implementations11 Apr 2016 Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, Yu Qiao

Face detection and alignment in unconstrained environment are challenging due to various poses, illuminations and occlusions.

Face Alignment Face Detection

From Facial Expression Recognition to Interpersonal Relation Prediction

no code implementations21 Sep 2016 Zhanpeng Zhang, Ping Luo, Chen Change Loy, Xiaoou Tang

Unlike existing models that typically learn from facial expression labels alone, we devise an effective multitask network that is capable of learning from rich auxiliary attributes such as gender, age, and head pose, beyond just facial expression data.

Attribute Facial Expression Recognition +2

Detecting Faces Using Inside Cascaded Contextual CNN

no code implementations ICCV 2017 Kaipeng Zhang, Zhanpeng Zhang, Hao Wang, Zhifeng Li, Yu Qiao, Wei Liu

Deep Convolutional Neural Networks (CNNs) achieve substantial improvements in face detection in the wild.

Face Detection

Super-Identity Convolutional Neural Network for Face Hallucination

no code implementations ECCV 2018 Kaipeng Zhang, Zhanpeng Zhang, Chia-Wen Cheng, Winston H. Hsu, Yu Qiao, Wei Liu, Tong Zhang

Face hallucination is a generative task to super-resolve the facial image with low resolution while human perception of face heavily relies on identity information.

Face Generation Face Hallucination +1

MetaGrasp: Data Efficient Grasping by Affordance Interpreter Network

no code implementations18 Feb 2019 Junhao Cai, Hui Cheng, Zhanpeng Zhang, Jingcheng Su

Although the model is trained using only RGB image, when changing the background textures, it also performs well and can achieve even 94% accuracy on the set of adversarial objects, which outperforms current state-of-the-art methods.

Multi-modality Latent Interaction Network for Visual Question Answering

no code implementations ICCV 2019 Peng Gao, Haoxuan You, Zhanpeng Zhang, Xiaogang Wang, Hongsheng Li

The proposed module learns the cross-modality relationships between latent visual and language summarizations, which summarize visual regions and question into a small number of latent representations to avoid modeling uninformative individual region-word relations.

Language Modelling Question Answering +1

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