- 2 Facial Action Unit Detection Using Kernel Partial Least Squares
- 5 3D Twins and Expression Challenge
- 6 Static Facial Expression In The Wild: Data, Evaluation Protocol And Benchmark
- 10 UMB-DB: A Database of Partially Occluded 3D Faces
- 12 A Face Biometric Benchmarking Review and Characterisation
- 13 High-Resolution Comprehensive 3-D Dynamic Database for Facial Articulation Analysis
- 15 Manifold Based Sparse Representation for Robust Expression Recognition without Neutral Subtraction
- 18 Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization
- 19 Single- and Cross- Database Benchmarks for Gender Classification Under Unconstrained Settings
- 24 Evaluation of face recognition system in hetergenous environments (visible vs NIR)
- 29 High Quality Facial Expression Recognition in Video Streams using Shape Related Information only
- 31 VADANA: A dense dataset for facial image analysis
- 34 Face Detection using SURF Cascade
- 35 Criteria and metrics for thresholded AU detection
- 36 Object Representation Based on Gabor Wave Vector Bining : An Application to Human Head Pose Detection
In the past decades, facial image analysis has attracted continuous attention in computer vision, pattern recognition and machine learning areas, owing to its scientific challenges in both psychological interpretation and computational simulation, as well as its huge potentials in real-world applications. Much progress has been achieved in the last decades; however, researchers in the field also meet bafflement and challenges on the comprehensive and unbiased evaluation of the related technologies, which may prevent them from discovering the actual state of the art.
BeFIT –Benchmarking Facial Image Analysis Technologies– is an international collaborative effort on standardizing the evaluation of facial image analysis technologies. The objective is to bring together different face analysis evaluations and provide a medium for researchers to discuss about different aspects of face analysis. Sample categories are:
- Face Detection and Tracking
- Face Detection
- Face Tracking
- Face Alignment
- Facial Feature Localization
- Face Alignment
- Face Image Enhancement
- Super-resolution of Face Images
- Image Quality Enhancement
- Illumination Normalization
- 3D Face Reconstruction from 2D View(s)
- Face Recognition
- Open- / Close-set Face Identification / Watch List Screening
- Face Verification / Face Re-Identification / Face Clustering
- Video-based Face Recognition
- High-resolution Face Recognition
- 3D Face Recognition
- Face Attributes Analysis
- Age Estimation
- Gender Classification
- Ethnicity Classification
- Glasses, Mustache, Beard Detection
- Facial Expression Analysis
- Action Unit Detection
- Emotion Classification
The workshop aims at encouraging researchers to run more standardized tests, to share data and to propose new challenges related to face analysis. It is of particular interest to have challenges with realistic data, containing illumination and view variations. The workshop will accept following type of paper submissions:
- Face analysis papers as long as they follow a standard benchmark process or the authors would share their own data that they have used for their experiments.
- Papers presenting new data sets and proposing new challenges.
- Papers that discuss the usefulness or inability of existing benchmarks.
For the first point, these benchmarks can be any that have been already used by the community, such as FERET, FRGC, LFW, FDDB, etc.
Paper Formatting: Papers are limited to eight pages. Please use the ICCV author kit to format the papers.
Blind review: Reviewing will be double blind. Please see the ICCV author kit for detailed explanations of how to ensure this.
Submission: Through BeFIT Online Submission System
Dual submission policy: Dual submission is allowed for the papers that have been submitted to
the main conference of ICCV 2011.