Face Detection
133 papers with code • 13 benchmarks • 36 datasets
Face Detection is a computer vision task that involves automatically identifying and locating human faces within digital images or videos. It is a fundamental technology that underpins many applications such as face recognition, face tracking, and facial analysis.
( Image credit: insightface )
Libraries
Use these libraries to find Face Detection models and implementationsLatest papers
Robust Human Identity Anonymization using Pose Estimation
Many outdoor autonomous mobile platforms require more human identity anonymized data to power their data-driven algorithms.
Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method
In this paper, we consider the task of low-light image enhancement (LLIE) and introduce a large-scale database consisting of images at 4K and 8K resolution.
Robustness Disparities in Face Detection
Many existing algorithmic audits examine the performance of these systems on later stage elements of facial analysis systems like facial recognition and age, emotion, or perceived gender prediction; however, a core component to these systems has been vastly understudied from a fairness perspective: face detection, sometimes called face localization.
Entropy-Driven Mixed-Precision Quantization for Deep Network Design
Deploying deep convolutional neural networks on Internet-of-Things (IoT) devices is challenging due to the limited computational resources, such as limited SRAM memory and Flash storage.
Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
Drawings are powerful means of pictorial abstraction and communication.
LAD-RCNN:A Powerful Tool for Livestock Face Detection and Normalization
However, there is no study on normalizing of the animal face image with arbitrary directions.
In Search of a Robust Facial Expressions Recognition Model: A Large-Scale Visual Cross-Corpus Study
Many researchers have been seeking robust emotion recognition system for already last two decades.
YOLO-FaceV2: A Scale and Occlusion Aware Face Detector
In this paper, we propose a real-time face detector based on the one-stage detector YOLOv5, named YOLO-FaceV2.
LPYOLO: Low Precision YOLO for Face Detection on FPGA
FPGAs are very low power, inclined to do parallel operations and deeply suitable devices for running Convolutional Neural Networks (CNN) which are the fundamental unit of an artificial intelligence application.
Classifying emotions and engagement in online learning based on a single facial expression recognition neural network
It is shown that the resulting facial features can be used for fast simultaneous prediction of students’ engagement levels (from disengaged to highly engaged), individual emotions (happy, sad, etc.,) and group-level affect (positive, neutral or negative).