SiW-Mv2 dataset contains 14 spoof types spanning from typical print and replay attack, to various masks, impersonation makeup and physical material coverings. SiW-Mv2 has the largest variance in terms of the spoof pattern, each of these patterns are designated and verified by the IARPA project. For example, obfuscation makeup and ...
Continue readingKeywords: Face antispoofing
The source code can be downloaded from here
Continue readingKeywords: 3D Shape Reconstruction, 3D Object Detection, Generic Object 3D Reconstruction
The source code can be downloaded from here
Continue readingKeywords: 3D Shape Reconstruction, Generic Object 3D Reconstruction
The source code can be downloaded from here
Continue readingKeywords: Depth Completion, Camera+LiDAR+Radar
Kinematic 3D implementation in Python and Pytorch can be downloaded from here.
If you use the Kinematic 3D code, please cite the ECCV 2020 paper.
Continue readingKeywords: 3D Object Detection
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 ...
Continue readingKeywords: Image Manipulation
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 ...
Continue readingKeywords: Image Manipulation
Biometric recognition is increasingly used in society for commercial applications and high-level security. However, recent works are not generalizable between the biometric modalities. We use live and spoof videos of generic objects to model the noise patterns for camera sensors and spoof mediums, and synthesize seen and unseen combinations of ...
Continue readingKeywords: Face antispoofing
Biometric recognition is increasingly used in society for commercial applications and high-level security. However, recent works are not generalizable between the biometric modalities. We collect the GOSet dataset to study content-independent anti-spoofing.
The GOSet dataset is available here.
Continue readingKeywords: Face antispoofing
3DFC implementation in Python and Pytorch may be downloaded from here.
Continue readingKeywords: 3D face modeling
M3D-RPN implementation in Python and Pytorch may be downloaded from here.
If you use M3D-RPN code, please cite the ICCV 2019 paper.
Continue readingKeywords: 3D Object Detection
To facilitate gait recognition research, we collect the Front-View Gait (FVG) database in the course of two years, 2017 and 2018. To better protect the privacy of the subjects, we create a version of the database called FVG-B where the face area is blurred to the extent that state-of-the-art face ...
Continue readingKeywords: Gait Recognition
Deep Tree Network implementation may be downloaded from here.
Face De-Spoofing implementation may be downloaded from here.
STDN(On Disentangling Spoof Traces for Generic Face Anti-Spoofing) implementation may be downloaded from here.
If you use MSU PAD code, please cite to the papers:
Continue readingKeywords: Face Antispoofing
AR-Ped implementation in Matlab and Caffe may be downloaded from here.
If you use AR-Ped code, please cite the CVPR 2019 paper.
Continue readingKeywords: Pedestrian Detection
Recurrent Flow-Guided Semantic Forecasting implementation in python and caffe may be downloaded from here.
If you use the segmentation forecasting code, please cite the WACV 2019 paper.
Continue readingKeywords: Forecasting, Semantic Segmentation
You can download the Depth Coefficients Source Code from here.
Continue readingKeywords: Depth Completion, 3D Object Detection
The training, testing code, and pre-trianed model are available at here
Continue readingKeywords: Face recognition
Source code of Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos may be downloaded from here.
If you use 3D Face Reconstruction code, please cite to the papers:
Continue readingYou can download the LFW from here and AFLW200 from here.
References:
[1] Tal Hassner, Shai Harel, Eran Paz, and Roee Enbar. Effective face frontalization in unconstrained images. In CVPR, 2015
[2] Xiangyu Zhu, Zhen Lei, Junjie Yan, Dong Yi, and Stan Z. Li. High-fidelity pose and expression normalization for ...
Continue readingKeywords: Face Recognition, Face Reconstruction
CVPR 2017 source code may be downloaded from here.
If you use the code, please cite to the papers:
Continue readingKeywords: Data Imputation, Multi-modality
You can download the Nonlinear 3D Face Morphable Model Source Code from here.
Continue readingKeywords: Face Alignment, Face Reconstruction
With the advance of sensor technology, existing antispoofing systems can be vulnerable to emerging high-quality spoof mediums. One way to make the system robust to these attacks is to collect new high-quality databases. In response to this need, we collect a new face anti-spoofing database named Spoof in the Wild ...
Continue readingKeywords: Face antispoofing
You can download the OEP dataset from here.
If you use OEP dataset, please cite the paper:
Continue readingKeywords: Application
You can download the Multi-Task CNN Source Code from here.
Continue readingKeywords: Face Recognition
SDS-RCNN implementation in Matlab and Caffe may be downloaded from here.
If you use SDS-RCNN code, please cite the ICCV 2017 paper.
Continue readingKeywords: Pedestrian Detection
DR-GAN face frontalization demo can be found here.
Source code is available here.
Tensorflow pre-trained model can be download here.
Frontalized faces and feature representations of faces from benchmark datasets may be downloaded at: CFP and IJB-A.
If you use these results, please cite to the papers:
Continue readingKeywords: Face Recognition, Face Reconstruction
Dense Face Alignment implementation may be downloaded from here.
Pose-Invariant Face Alignment with a Single CNN implementation may be downloaded from here.
PIFA implementation may be downloaded from here.
The part of AFLW database used for training and testing can be found from here.
If you use PIFA code, please ...
Continue readingKeywords: Face alignment
TRGMC implementation in Matlab may be downloaded from here.
This project was supported by the research gift from TechSmith Inc.
If you use TRGMC code, please cite to the ECCV 2016 paper:
Continue readingKeywords: Motion Compensation, Activity Recognition
3D Face Reconstruction binary code may be downloaded from here.
If you use 3D Face Reconstruction code, please cite to the papers:
Continue readingKeywords: Face reconstruction
RGMC implementation in Matlab may be downloaded from here.
This project was supported by the research gift from TechSmith Inc.
If you use RGMC code, please cite to the BMVC 2015 paper:
Continue readingKeywords: Motion Compensation, Activity Recognition
The database can be downloaded from here. It includes three parts:
Please cite the following paper if you use this database:
Continue readingKeywords: Plant Vision, Database
Citation
If you use SVW dataset, please refer to this paper in your publications: Continue reading
Keywords: Database, Activity Recognition
You can download the 200-image gallery/test dataset from here.
If you use APFD dataset, please cite to the paper:
Continue readingKeywords: Face deidentification
This dataset is released in two different forms. Acoustics: 45 subjects from phase 1. Visual: Full dataset. Typing Behavior Dataset may be downloaded from here.
We collect a first-of-its kind keystroke database in two phases. Phase 1 includes 56 subjects typing multiple same day, fixed and free text, sessions. It ...
Continue readingKeywords: Typing behavior
Plant vision source code may be downloaded from here.
If you use the code, please cite to the papers:
Continue readingKeywords: Plant vision
