1 code implementation • NAACL 2022 • Yibo Hu, MohammadSaleh Hosseini, Erick Skorupa Parolin, Javier Osorio, Latifur Khan, Patrick Brandt, Vito D’Orazio
To help advance research in political science, we introduce ConfliBERT, a domain-specific pre-trained language model for conflict and political violence.
no code implementations • ECCV 2020 • Pei-Pei Li, Huaibo Huang, Yibo Hu, Xiang Wu, Ran He, Zhenan Sun
To explore the age effects on facial images, we propose a Disentangled Adversarial Autoencoder (DAAE) to disentangle the facial images into three independent factors: age, identity and extraneous information.
1 code implementation • 19 Oct 2023 • Yiqiao Jin, Mohit Chandra, Gaurav Verma, Yibo Hu, Munmun De Choudhury, Srijan Kumar
Our findings underscore the pressing need to bolster the cross-lingual capacities of these models, and to provide an equitable information ecosystem accessible to all.
no code implementations • 8 Oct 2023 • Peipei Li, Xing Cui, Yibo Hu, Man Zhang, Ting Yao, Tao Mei
Directly employing small models may result in a significant drop in performance since it is difficult for a small model to adequately capture local structure and global shape information simultaneously, which are essential clues for point cloud analysis.
1 code implementation • 15 Aug 2023 • Yibo Hu, Erick Skorupa Parolin, Latifur Khan, Patrick T. Brandt, Javier Osorio, Vito J. D'Orazio
Our study underscores the efficacy of leveraging transfer learning and existing expertise to enhance research efficiency and scalability in this area.
no code implementations • 20 Mar 2023 • Xing Cui, Zekun Li, Peipei Li, Yibo Hu, Hailin Shi, Zhaofeng He
This paper explores interactive facial image editing via dialogue and introduces the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this context.
1 code implementation • 18 Oct 2022 • Yibo Hu, Yu Lin, Erick Skorupa Parolin, Latifur Khan, Kevin Hamlen
Recent works in cyber deception study how to deter malicious intrusion by generating multiple fake versions of a critical document to impose costs on adversaries who need to identify the correct information.
no code implementations • 19 Sep 2022 • Hailin Shi, Hang Du, Yibo Hu, Jun Wang, Dan Zeng, Ting Yao
Such multi-shot scheme brings inference burden, and the predefined scales inevitably have gap from real data.
1 code implementation • 1 Dec 2021 • Hangtong Wu, Dan Zen, Yibo Hu, Hailin Shi, Tao Mei
Such noisy samples are hard to predict precise depth values, thus may obstruct the widely-used depth supervised optimization.
1 code implementation • 15 Jul 2021 • Yibo Hu, Latifur Khan
Extensive empirical experiments demonstrate that our model based on evidential uncertainty outperforms other counterparts for detecting OOD examples.
no code implementations • 10 May 2021 • Hailin Shi, Dan Zeng, Yichun Tai, Hang Du, Yibo Hu, ZiCheng Zhang, Tao Mei
However, unlike the existing public face datasets, in many real-world scenarios of face recognition, the depth of training dataset is shallow, which means only two face images are available for each ID.
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)
1 code implementation • ICCV 2021 • Chaoyou Fu, Yibo Hu, Xiang Wu, Hailin Shi, Tao Mei, Ran He
Visible-Infrared person re-identification (VI-ReID) aims to match cross-modality pedestrian images, breaking through the limitation of single-modality person ReID in dark environment.
2 code implementations • 12 Jan 2021 • Jun Wang, Yinglu Liu, Yibo Hu, Hailin Shi, Tao Mei
For example, the production of face representation network desires a modular training scheme to consider the proper choice from various candidates of state-of-the-art backbone and training supervision subject to the real-world face recognition demand; for performance analysis and comparison, the standard and automatic evaluation with a bunch of models on multiple benchmarks will be a desired tool as well; besides, a public groundwork is welcomed for deploying the face recognition in the shape of holistic pipeline.
1 code implementation • 26 Dec 2020 • Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen
By considering the multidimensional uncertainty, we proposed a novel uncertainty-aware evidential NN called WGAN-ENN (WENN) for solving an out-of-distribution (OOD) detection problem.
Generative Adversarial Network Multi-class Classification +3
1 code implementation • 20 Sep 2020 • Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He
As a consequence, massive new diverse paired heterogeneous images with the same identity can be generated from noises.
1 code implementation • ECCV 2020 • Yibo Hu, Xiang Wu, Ran He
In this paper, we rethink three freedoms of differentiable NAS, i. e. operation-level, depth-level and width-level, and propose a novel method, named Three-Freedom NAS (TF-NAS), to achieve both good classification accuracy and precise latency constraint.
no code implementations • NeurIPS 2019 • Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He
Specifically, we first introduce a dual variational autoencoder to represent a joint distribution of paired heterogeneous images.
no code implementations • 30 Mar 2019 • Pei-Pei Li, Xiang Wu, Yibo Hu, Ran He, Zhenan Sun
In this paper, a new large-scale Multi-yaw Multi-pitch high-quality database is proposed for Facial Pose Analysis (M2FPA), including face frontalization, face rotation, facial pose estimation and pose-invariant face recognition.
no code implementations • 30 Mar 2019 • Pei-Pei Li, Huaibo Huang, Yibo Hu, Xiang Wu, Ran He, Zhenan Sun
UVA is the first attempt to achieve facial age analysis tasks, including age translation, age generation and age estimation, in a universal framework.
no code implementations • 28 Mar 2019 • Chaoyou Fu, Yibo Hu, Xiang Wu, Guoli Wang, Qian Zhang, Ran He
Furthermore, due to the lack of high-resolution face manipulation databases to verify the effectiveness of our method, we collect a new high-quality Multi-View Face (MVF-HQ) database.
1 code implementation • 25 Mar 2019 • Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He
Then, in order to ensure the identity consistency of the generated paired heterogeneous images, we impose a distribution alignment in the latent space and a pairwise identity preserving in the image space.
Ranked #1 on Face Verification on CASIA NIR-VIS 2.0
no code implementations • 20 Sep 2018 • Pei-Pei Li, Yibo Hu, Ran He, Zhenan Sun
%Moreover, to achieve accurate age generation under the premise of preserving the identity information, age estimation network and face verification network are employed.
no code implementations • 20 Sep 2018 • Pei-Pei Li, Yibo Hu, Ran He, Zhenan Sun
Inspired by the biological evolutionary mechanism, we propose a Coupled Evolutionary Network (CEN) with two concurrent evolutionary processes: evolutionary label distribution learning and evolutionary slack regression.
no code implementations • 9 Sep 2018 • Linsen Song, Jie Cao, Linxiao Song, Yibo Hu, Ran He
Extensive experimental results qualitatively and quantitatively demonstrate that our network is able to generate visually pleasing face completion results and edit face attributes as well.
no code implementations • NeurIPS 2018 • Jie Cao, Yibo Hu, Hongwen Zhang, Ran He, Zhenan Sun
We decompose the prerequisite of warping into dense correspondence field estimation and facial texture map recovering, which are both well addressed by deep networks.
no code implementations • CVPR 2018 • Yibo Hu, Xiang Wu, Bing Yu, Ran He, Zhenan Sun
Face rotation provides an effective and cheap way for data augmentation and representation learning of face recognition.
no code implementations • 21 Feb 2018 • Jie Cao, Yibo Hu, Bing Yu, Ran He, Zhenan Sun
Multi-view face synthesis from a single image is an ill-posed problem and often suffers from serious appearance distortion.
no code implementations • 25 Jan 2018 • Pei-Pei Li, Yibo Hu, Qi Li, Ran He, Zhenan Sun
To utilize both global and local facial information, we propose a Global and Local Consistent Age Generative Adversarial Network (GLCA-GAN).
no code implementations • 13 Dec 2017 • Zhihang Li, Yibo Hu, Ran He
We treat the face completion and corruption as disentangling and fusing processes of clean faces and occlusions, and propose a jointly disentangling and fusing Generative Adversarial Network (DF-GAN).
no code implementations • 12 Apr 2017 • Yibo Hu, Xiang Wu, Ran He
In this paper, we propose a novel Attention-Set based Metric Learning (ASML) method to measure the statistical characteristics of image sets.