1. 

   Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification

   Feng Liu, Minchul Kim, Ziang Gu, Anil Jain, Xiaoming Liu

   Long-Term Person Re-Identification (LT-ReID) has become increasingly crucial in computer vision and biometrics. In this work, we aim to extend LT-ReID beyond pedestrian recognition to include a wider range of real-world human activities while still accounting for cloth-changing scenarios over large time gaps. This setting poses additional challenges due to ...

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   Keywords: Body Matching, 3D Shape Reconstruction, Biometrics, 3D Human Reconstruction, Person Re-identification

2. 

   Controllable and Guided Face Synthesis for Unconstrained Face Recognition

   Feng Liu, Minchul Kim, Anil Jain, Xiaoming Liu

   Although significant advances have been made in face recognition (FR), FR in unconstrained environments remains challenging due to the domain gap between the semi-constrained training datasets and unconstrained testing scenarios. To address this problem, we propose a controllable face synthesis model (CFSM) that can mimic the distribution of target datasets ...

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   Keywords: Face Recognition, Face Synthesis, Biometrics

3. 

   2D GANs Meet Unsupervised Single-View 3D Reconstruction

   Feng Liu, Xiaoming Liu

   Recent research has shown that controllable image generation based on pre-trained GANs can benefit a wide range of computer vision tasks. However, less attention has been devoted to 3D vision tasks. In light of this, we propose a novel image-conditioned neural implicit field, which can leverage 2D supervisions from GAN-generated ...

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   Keywords: 3D Shape Reconstruction, Generic Object 3D Reconstruction

4. 

   Cluster and Aggregate: Face Recognition with Large Probe Set

   Minchul Kim, Feng Liu, Anil K. Jain, Xiaoming Liu

   Feature fusion plays a crucial role in unconstrained face recognition where inputs (probes) comprise of a set of N low quality images whose individual qualities vary. Advances in attention and recurrent modules have led to feature fusion that can model the relationship among the images in the input set. However ...

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   Keywords: Face recognition, Biometrics

5. 

   Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image

   Feng Liu, Xiaoming Liu

   Inferring 3D locations and shapes of multiple objects from a single 2D image is a long-standing objective of computer vision. Most of the existing works either predict one of these 3D properties or focus on solving both for a single object. One fundamental challenge lies in how to learn an ...

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   Keywords: 3D Object Detection, 3D Shape Reconstruction, Generic Object 3D Reconstruction

6. 

   Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction

   Feng Liu, Luan Tran, Xiaoming Liu

   Inferring 3D structure of a generic object from a 2D image is a long-standing objective of computer vision. Conventional approaches either learn completely from CAD-generated synthetic data, which have difficulty in inference from real images, or generate 2.5D depth image via intrinsic decomposition, which is limited compared to the ...

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   Keywords: Generic Object 3D Reconstruction, 3D Shape Reconstruction, Semantic Segmentation

7. 

   Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence

   Feng Liu, Xiaoming Liu

   The goal of this paper is to learn dense 3D shape correspondence for topology-varying objects in an unsupervised manner. Conventional implicit functions estimate the occupancy of a 3D point given a shape latent code. Instead, our novel implicit function produces a part embedding vector for each 3D point, which is ...

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   Keywords: 3D Shape Correspondence, Semantic Segmentation

8. 

   Facial Forgery Detection

   Hao Dang*, Feng Liu*, Joel Stehouwer*, Xiaoming Liu, Anil Jain

   The prevalence of facial recognition, biometric unlock, and social media presents a significant opportunity for bad actors to introduce forged or manipulated images to spread false information or damage reputations. This is aided by the continuing improvement in realistic image synthesis and manipulation by generative adversarial network, GAN, based methods ...

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   Keywords: Image Manipulation, Low-level Vision, Database

9. 

   3D Face Modeling from Diverse Raw Scan Data

   Feng Liu, Luan Tran, Xiaoming Liu

   Traditional 3D face models learn a latent representation of faces using linear subspaces from no more than 300 training scans of a single database. The main roadblock of building a large-scale face model from diverse 3D databases lies in the lack of dense correspondence among raw scans. To address these ...

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   Keywords: 3D Face Modeling, Face Reconstruction, 3D Shape Reconstruction

2024

• Distilling CLIP with Dual Guidance for Learning Discriminative Human Body Shape Representation
  Feng Liu, Minchul Kim, Zhiyuan Ren, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2024), Seattle, WA, Jun. 2024
  Bibtex | PDF | Supplemental
@inproceedings{ distilling-clip-with-dual-guidance-for-learning-discriminative-human-body-shape-representation,
  author = { Feng Liu and Minchul Kim and Zhiyuan Ren and Xiaoming Liu },
  title = { Distilling CLIP with Dual Guidance for Learning Discriminative Human Body Shape Representation },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Seattle, WA },
  month = { June },
  year = { 2024 },
}
• KeyPoint Relative Position Encoding for Face Recognition
  Minchul Kim, Yiyang Su, Feng Liu, Anil Jain, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2024), Seattle, WA, Jun. 2024
  Bibtex | PDF | arXiv | Supplemental | Code
@inproceedings{ keypoint-relative-position-encoding-for-face-recognition,
  author = { Minchul Kim and Yiyang Su and Feng Liu and Anil Jain and Xiaoming Liu },
  title = { KeyPoint Relative Position Encoding for Face Recognition },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Seattle, WA },
  month = { June },
  year = { 2024 },
}
• TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion Process
  Zhiyuan Ren, Minchul Kim, Feng Liu, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2024), Seattle, WA, Jun. 2024
  Bibtex | PDF | Supplemental | Code
@inproceedings{ tiger-time-varying-denoising-model-for-3d-point-cloud-generation-with-diffusion-process,
  author = { Zhiyuan Ren and Minchul Kim and Feng Liu and Xiaoming Liu },
  title = { TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion Process },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Seattle, WA },
  month = { June },
  year = { 2024 },
}
• FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
  Feng Liu, Ryan Ashbaugh, Nicholas Chimitt, Najmul Hassan, Ali Hassani, Ajay Jaiswal, Minchul Kim, Zhiyuan Mao, Christopher Perry, Zhiyuan Ren, Yiyang Su, Pegah Varghaei, Kai Wang, Xingguang Zhang, Stanley Chan, Arun Ross, Humphrey Shi, Zhangyang Wang, Anil Jain, Xiaoming Liu
  In Proceeding of Winter Conference on Applications of Computer Vision (WACV 2024), Waikoloa, Hawaii, Jan. 2024
  Bibtex | PDF | arXiv
@inproceedings{ farsight-a-physics-driven-whole-body-biometric-system-at-large-distance-and-altitude,
  author = { Feng Liu and Ryan Ashbaugh and Nicholas Chimitt and Najmul Hassan and Ali Hassani and Ajay Jaiswal and Minchul Kim and Zhiyuan Mao and Christopher Perry and Zhiyuan Ren and Yiyang Su and Pegah Varghaei and Kai Wang and Xingguang Zhang and Stanley Chan and Arun Ross and Humphrey Shi and Zhangyang Wang and Anil Jain and Xiaoming Liu },
  title = { FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude },
  booktitle = { In Proceeding of Winter Conference on Applications of Computer Vision },
  address = { Waikoloa, Hawaii },
  month = { January },
  year = { 2024 },
}

2023

• Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification
  Feng Liu, Minchul Kim, ZiAng Gu, Anil Jain, Xiaoming Liu
  In Proceeding of International Conference on Computer Vision (ICCV 2023), Paris, France, Oct. 2023
  Bibtex | PDF | arXiv | Project Webpage | Code
@inproceedings{ learning-clothing-and-pose-invariant-3d-shape-representation-for-long-term-person-re-identification,
  author = { Feng Liu and Minchul Kim and ZiAng Gu and Anil Jain and Xiaoming Liu },
  title = { Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification },
  booktitle = { In Proceeding of International Conference on Computer Vision },
  address = { Paris, France },
  month = { October },
  year = { 2023 },
}
• DCFace: Synthetic Face Generation with Dual Condition Diffusion Model
  Minchul Kim, Feng Liu, Anil Jain, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, Jun. 2023
  Bibtex | PDF | Supplemental
@inproceedings{ dcface-synthetic-face-generation-with-dual-condition-diffusion-model,
  author = { Minchul Kim and Feng Liu and Anil Jain and Xiaoming Liu },
  title = { DCFace: Synthetic Face Generation with Dual Condition Diffusion Model },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Vancouver, Canada },
  month = { June },
  year = { 2023 },
}
• INFAMOUS-NeRF: ImproviNg FAce MOdeling Using Semantically-Aligned Hypernetworks with Neural Radiance Fields
  Andrew Hou, Feng Liu, Zhiyuan Ren, Michel Sarkis, Ning Bi, Yiying Tong, Xiaoming Liu
  arxiv, Dec. 2023
  Bibtex | arXiv
@inproceedings{ infamous-nerf-improving-face-modeling-using-semantically-aligned-hypernetworks-with-neural-radiance-fields,
  author = { Andrew Hou and Feng Liu and Zhiyuan Ren and Michel Sarkis and Ning Bi and Yiying Tong and Xiaoming Liu },
  title = { INFAMOUS-NeRF: ImproviNg FAce MOdeling Using Semantically-Aligned Hypernetworks with Neural Radiance Fields },
  booktitle = { arxiv },
  address = { },
  month = { December },
  year = { 2023 },
}
• AG-ReID 2023: Aerial-Ground Person Re-identification Challenge Results
  Kien Nguyen, Clinton Fookes, Sridha Sridharan, Feng Liu, Xiaoming Liu, Arun Ross, Dana Michalski, Huy Nguyen, Debayan Deb, Mahak Kothari, Manisha Saini, Dawei Du, Scott McCloskey, Gabriel Bertocco, Fernanda Andal´o, Terrance E. Boult, Anderson Rocha, Haidong Zhu, Zhaoheng Zheng, Ram Nevatia, Zaigham Randhawa, Sinan Sabri, Gianfranco Doretto
  In Proceeding of International Joint Conference on Biometrics (IJCB 2023), Ljubljana, Slovenia, Sep. 2023
  Bibtex | PDF
@inproceedings{ ag-reid-2023-aerial-ground-person-re-identification-challenge-results,
  author = { Kien Nguyen and Clinton Fookes and Sridha Sridharan and Feng Liu and Xiaoming Liu and Arun Ross and Dana Michalski and Huy Nguyen and Debayan Deb and Mahak Kothari and Manisha Saini and Dawei Du and Scott McCloskey and Gabriel Bertocco and Fernanda Andal´o and Terrance E. Boult and Anderson Rocha and Haidong Zhu and Zhaoheng Zheng and Ram Nevatia and Zaigham Randhawa and Sinan Sabri and Gianfranco Doretto },
  title = { AG-ReID 2023: Aerial-Ground Person Re-identification Challenge Results },
  booktitle = { In Proceeding of International Joint Conference on Biometrics },
  address = { Ljubljana, Slovenia },
  month = { September },
  year = { 2023 },
}

2022

• Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects
  Feng Liu, Xiaoming Liu
  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), , Nov. 2022 (in press)
  Bibtex | PDF | arXiv
@article{ learning-implicit-functions-for-dense-3d-shape-correspondence-of-generic-objects,
  author = { Feng Liu and Xiaoming Liu },
  title = { Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects },
  journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) },
  month = { November },
  year = { 2022 },
}
• The State of Aerial Surveillance: A Survey
  Kien Nguyen, Clinton Fookes, Sridha Sridharan, Yingli Tian, Feng Liu, Xiaoming Liu, Arun Ross
  IEEE Transactions on Pattern Analysis and Machine Intelligence, , Jan. 2022 (Under Review)
  Bibtex | PDF | arXiv
@article{ the-state-of-aerial-surveillance-a-survey,
  author = { Kien Nguyen and Clinton Fookes and Sridha Sridharan and Yingli Tian and Feng Liu and Xiaoming Liu and Arun Ross },
  title = { The State of Aerial Surveillance: A Survey },
  journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
  month = { January },
  year = { 2022 },
}
• Cluster and Aggregate: Face Recognition with Large Probe Set
  Minchul Kim, Feng Liu, Anil Jain, Xiaoming Liu
  In Proceeding of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, Dec. 2022
  Bibtex | PDF | arXiv | Supplemental | Project Webpage
@inproceedings{ cluster-and-aggregate-face-recognition-with-large-probe-set,
  author = { Minchul Kim and Feng Liu and Anil Jain and Xiaoming Liu },
  title = { Cluster and Aggregate: Face Recognition with Large Probe Set },
  booktitle = { In Proceeding of Thirty-sixth Conference on Neural Information Processing Systems },
  address = { New Orleans, LA },
  month = { December },
  year = { 2022 },
}
• 2D GANs Meet Unsupervised Single-View 3D Reconstruction
  Feng Liu, Xiaoming Liu
  In Proceeding of European Conference on Computer Vision (ECCV 2022), Tel-Aviv, Israel, Oct. 2022
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code
@inproceedings{ 2d-gans-meet-unsupervised-single-view-3d-reconstruction,
  author = { Feng Liu and Xiaoming Liu },
  title = { 2D GANs Meet Unsupervised Single-View 3D Reconstruction },
  booktitle = { In Proceeding of European Conference on Computer Vision },
  address = { Tel-Aviv, Israel },
  month = { October },
  year = { 2022 },
}
• Controllable and Guided Face Synthesis for Unconstrained Face Recognition
  Feng Liu, Minchul Kim, Anil Jain, Xiaoming Liu
  In Proceeding of European Conference on Computer Vision (ECCV 2022), Tel-Aviv, Israel, Oct. 2022
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code
@inproceedings{ controllable-and-guided-face-synthesis-for-unconstrained-face-recognition,
  author = { Feng Liu and Minchul Kim and Anil Jain and Xiaoming Liu },
  title = { Controllable and Guided Face Synthesis for Unconstrained Face Recognition },
  booktitle = { In Proceeding of European Conference on Computer Vision },
  address = { Tel-Aviv, Israel },
  month = { October },
  year = { 2022 },
}

2021

• Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation
  Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael Bronstein, Stefanos Zafeiriou
  International Journal of Computer Vision (IJCV), Vol. 129, pp.2680-2713, , Jun. 2021
  Bibtex | PDF
@article{ shape-my-face-registering-3d-face-scans-by-surface-to-surface-translation,
  author = { Mehdi Bahri and Eimear O' Sullivan and Shunwang Gong and Feng Liu and Xiaoming Liu and Michael Bronstein and Stefanos Zafeiriou },
  title = { Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation },
  journal = { International Journal of Computer Vision (IJCV) },
  volume = { 129 },
  month = { June },
  year = { 2021 },
  pages = { 2680--2713 },
}
• Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image
  Feng Liu, Xiaoming Liu
  In Proceeding of Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Virtual, Dec. 2021
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
@inproceedings{ voxel-based-3d-detection-and-reconstruction-of-multiple-objects-from-a-single-image,
  author = { Feng Liu and Xiaoming Liu },
  title = { Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image },
  booktitle = { In Proceeding of Thirty-fifth Conference on Neural Information Processing Systems },
  address = { Virtual },
  month = { December },
  year = { 2021 },
}
• Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction
  Feng Liu, Luan Tran, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, Jun. 2021
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
@inproceedings{ fully-understanding-generic-objects-modeling-segmentation-and-reconstruction,
  author = { Feng Liu and Luan Tran and Xiaoming Liu },
  title = { Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Nashville, TN },
  month = { June },
  year = { 2021 },
}

2020

• On Learning Disentangled Representations for Gait Recognition
  Ziyuan Zhang, Luan Tran, Feng Liu, Xiaoming Liu
  IEEE Transactions on Pattern Analysis and Machine Intelligence, , May. 2020 (in press)
  Bibtex | PDF | arXiv | Project Webpage | Code
@article{ on-learning-disentangled-representations-for-gait-recognition,
  author = { Ziyuan Zhang and Luan Tran and Feng Liu and Xiaoming Liu },
  title = { On Learning Disentangled Representations for Gait Recognition },
  journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
  month = { May },
  year = { 2020 },
}
• Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence
  Feng Liu, Xiaoming Liu
  In Proceeding of 2020 Conference on Neural Information Processing Systems (NeurIPS 2020), Virtual, Dec. 2020 (Oral)
  Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage | Code | Video
@inproceedings{ learning-implicit-functions-for-topology-varying-dense-3d-shape-correspondence,
  author = { Feng Liu and Xiaoming Liu },
  title = { Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence },
  booktitle = { In Proceeding of 2020 Conference on Neural Information Processing Systems },
  address = { Virtual },
  month = { December },
  year = { 2020 },
}
• On the Detection of Digital Face Manipulation
  Hao Dang*, Feng Liu*, Joel Stehouwer*, Xiaoming Liu, Anil Jain
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, Jun. 2020
  Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage | Code
@inproceedings{ on-the-detection-of-digital-face-manipulation,
  author = { Hao Dang* and Feng Liu* and Joel Stehouwer* and Xiaoming Liu and Anil Jain },
  title = { On the Detection of Digital Face Manipulation },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Seattle, WA },
  month = { June },
  year = { 2020 },
}

2019

• 3D Face Modeling from Diverse Raw Scan Data
  Feng Liu, Luan Tran, Xiaoming Liu
  In Proceeding of International Conference on Computer Vision (ICCV 2019), Seoul, South Korea, Oct. 2019 (Oral presentation)
  Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage | Code | Video
@inproceedings{ 3d-face-modeling-from-diverse-raw-scan-data,
  author = { Feng Liu and Luan Tran and Xiaoming Liu },
  title = { 3D Face Modeling from Diverse Raw Scan Data },
  booktitle = { In Proceeding of International Conference on Computer Vision },
  address = { Seoul, South Korea },
  month = { October },
  year = { 2019 },
}
• Towards High-fidelity Nonlinear 3D Face Morphable Model
  Luan Tran, Feng Liu, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019
  Bibtex | PDF | arXiv | Poster | Project Webpage | Code
@inproceedings{ towards-high-fidelity-nonlinear-3d-face-morphable-model,
  author = { Luan Tran and Feng Liu and Xiaoming Liu },
  title = { Towards High-fidelity Nonlinear 3D Face Morphable Model },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Long Beach, CA },
  month = { June },
  year = { 2019 },
}

2018

• Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition
  Feng Liu, Qijun Zhao, Xiaoming Liu, Dan Zeng
  IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 42, No. 3, pp.664-678, , Nov. 2018
  Bibtex | PDF | arXiv
@article{ joint-face-alignment-and-3d-face-reconstruction-with-application-to-face-recognition,
  author = { Feng Liu and Qijun Zhao and Xiaoming Liu and Dan Zeng },
  title = { Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition },
  journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
  volume = { 42 },
  number = { 3 },
  month = { November },
  year = { 2018 },
  pages = { 664--678 },
}
• Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition
  Feng Liu, Dan Zeng, Qijun Zhao, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, UT, Jun. 2018
  Bibtex | PDF | Supplemental | Poster
@inproceedings{ disentangling-features-in-3d-face-shapes-for-joint-face-reconstruction-and-recognition,
  author = { Feng Liu and Dan Zeng and Qijun Zhao and Xiaoming Liu },
  title = { Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Salt Lake City, UT },
  month = { June },
  year = { 2018 },
}

2016

• Joint Face Alignment and 3D Face Reconstruction
  Feng Liu, Dan Zeng, Qijun Zhao, Xiaoming Liu
  Proc. European Conference on Computer Vision (ECCV 2016), Amsterdam, The Netherlands, Oct. 2016 (Spotlight presentation)
  Bibtex | PDF
@inproceedings{ joint-face-alignment-and-3d-face-reconstruction,
  author = { Feng Liu and Dan Zeng and Qijun Zhao and Xiaoming Liu },
  title = { Joint Face Alignment and 3D Face Reconstruction },
  booktitle = { Proc. European Conference on Computer Vision },
  address = { Amsterdam, The Netherlands },
  month = { October },
  year = { 2016 },
}