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.
Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
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.