3D Face Modelling
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yzy-stack/effort-aigi-detection
공식 코드Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection
https://github.com/yzyouzhang/asvspoof2021_air
공식 코드UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
https://github.com/zamdimon/distortion-generator
공식 코드Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings
https://github.com/zblasingame/DiM
공식 코드Leveraging Diffusion For Strong and High Quality Face Morphing Attacks
https://github.com/zblasingame/Greedy-DiM
공식 코드Greedy-DiM: Greedy Algorithms for Unreasonably Effective Face Morphs
https://github.com/zczcwh/poster
공식 코드POSTER: A Pyramid Cross-Fusion Transformer Network for Facial Expression Recognition
https://github.com/zdhnarsil/stochastic-marginal-actor-critic
공식 코드Latent State Marginalization as a Low-cost Approach for Improving Exploration
https://github.com/zengbohan0217/FNeVR
공식 코드https://github.com/zengbohan0217/fadm
공식 코드https://github.com/zengqunzhao/exp-clip
공식 코드Enhancing Zero-Shot Facial Expression Recognition by LLM Knowledge Transfer
https://github.com/zeroqiaoba/gpt4v-emotion
공식 코드GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition
https://github.com/zerosansan/fg2020_abaw
공식 코드Deep Convolutional Neural Network Based Facial Expression Recognition in the Wild
https://github.com/zfkarl/leaf
공식 코드LEAF: Unveiling Two Sides of the Same Coin in Semi-supervised Facial Expression Recognition
https://github.com/zhangchenxu528/FACIAL
공식 코드FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning
https://github.com/zhangdatalab/chgat
공식 코드https://github.com/zhangmenghe/mediapipe
공식 코드FaceAtlasAR: Atlas of Facial Acupuncture Points in Augmented Reality
https://github.com/zhangqianhui/tt-gnerf
공식 코드https://github.com/zhangxz1123/FilteredPolicyGradient
공식 코드https://github.com/zhao-zilong/MotivationCaseStudies
공식 코드Enhancing Robustness of On-line Learning Models on Highly Noisy Data
https://github.com/zhaolingao/rebel
공식 코드REBEL: Reinforcement Learning via Regressing Relative Rewards
https://github.com/zhaoweicai/mscnn
공식 코드A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection
https://github.com/zhaoyuzhi/childpredictor
공식 코드ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
https://github.com/zhelishisongjie/ssfer
공식 코드https://github.com/zhenglab/ffdbackbone
공식 코드https://github.com/zhenglinzhou/star
공식 코드STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection
https://github.com/zhenglisec/decision-based-mia
공식 코드https://github.com/zhenglisec/unganable
공식 코드https://github.com/zhengqinlai/imer-benchmark
공식 코드https://github.com/zhichaowang970201/text-to-video
공식 코드Text-to-Video: a Two-stage Framework for Zero-shot Identity-agnostic Talking-head Generation
https://github.com/zhihanyang2022/off-policy-continuous-control
공식 코드Recurrent Off-policy Baselines for Memory-based Continuous Control
https://github.com/zhihengli-UR/DebiAN
공식 코드Discover and Mitigate Unknown Biases with Debiasing Alternate Networks
https://github.com/zhipeixu/fakeshield
공식 코드https://github.com/zhiqiangdon/CU-Net
공식 코드Quantized Densely Connected U-Nets for Efficient Landmark Localization
https://github.com/zhiqic/keyposs
공식 코드KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration
https://github.com/zhiwenshao/ac2d
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.