https://github.com/xinqi-fan/ABAW2021
공식 코드Spatial and Temporal Networks for Facial Expression Recognition in the Wild Videos
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Spatial and Temporal Networks for Facial Expression Recognition in the Wild Videos
Generalizable Method for Face Anti-Spoofing with Semi-Supervised Learning
Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition
AU-aware graph convolutional network for Macro- and Micro-expression spotting
OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression
Building Age Estimation: A New Multi-Modal Benchmark Dataset and Community Challenge
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
Learning Pairwise Interaction for Generalizable DeepFake Detection
VoD: Learning Volume of Differences for Video-Based Deepfake Detection
EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning
Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition
Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake Detection
Boosting the Adversarial Transferability of Surrogate Models with Dark Knowledge
Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis
Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection
ReliableSwap: Boosting General Face Swapping Via Reliable Supervision
RestorerID: Towards Tuning-Free Face Restoration with ID Preservation
Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning
Face recognition via compact second order image gradient orientations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.