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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/kgrm/face-recog-eval

공식 코드

Strengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations

https://github.com/khalilimahdi/loss_balancing_icml2023

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Loss Balancing for Fair Supervised Learning

https://github.com/khawar-islam/fpvt

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Face Pyramid Vision Transformer

https://github.com/khurramHashmi/FeatEnHancer

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FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision

https://github.com/kim1102/IG-FIQA

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IG-FIQA: Improving Face Image Quality Assessment through Intra-class Variance Guidance robust to Inaccurate Pseudo-Labels

https://github.com/kim1102/VIGFace

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VIGFace: Virtual Identity Generation for Privacy-Free Face Recognition

https://github.com/kindredresearch/SenseAct

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Benchmarking Reinforcement Learning Algorithms on Real-World Robots

https://github.com/kindredresearch/arp

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Autoregressive Policies for Continuous Control Deep Reinforcement Learning

https://github.com/kjanjua26/Git-Loss-For-Deep-Face-Recognition

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Git Loss for Deep Face Recognition

https://github.com/kk7nc/RMDL

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RMDL: Random Multimodel Deep Learning for Classification

https://github.com/kkkcx/diffender

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DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks

https://github.com/kngwyu/infomax-option-critic

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Learning Diverse Options via InfoMax Termination Critic

https://github.com/konstantinkobs/SimLoss

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SimLoss: Class Similarities in Cross Entropy

https://github.com/konwook/mticl

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Learning Shared Safety Constraints from Multi-task Demonstrations

https://github.com/koulanurag/dream-and-search

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Dream and Search to Control: Latent Space Planning for Continuous Control

https://github.com/koushiksrivats/flip

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FLIP: Cross-domain Face Anti-spoofing with Language Guidance

https://github.com/krasjet-yu/yolo-facev2

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YOLO-FaceV2: A Scale and Occlusion Aware Face Detector

https://github.com/ksasi/fairDL

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On Biased Behavior of GANs for Face Verification

https://github.com/kuhnkeF/ABAW2020TNT

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Two-Stream Aural-Visual Affect Analysis in the Wild

https://github.com/kunkunlin1221/InstructFLIP

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InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing

https://github.com/kwanyun/FFaceNeRF

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FFaceNeRF: Few-shot Face Editing in Neural Radiance Fields

https://github.com/kwanyun/LeGO_code

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LeGO: Leveraging a Surface Deformation Network for Animatable Stylized Face Generation with One Example

https://github.com/kwanyun/StyleSketch

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Stylized Face Sketch Extraction via Generative Prior with Limited Data

https://github.com/l8cv/busterx

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BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation

https://github.com/laiyingxin2/dadf

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Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization

https://github.com/laiyingxin2/gm-df

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GM-DF: Generalized Multi-Scenario Deepfake Detection

https://github.com/laiyingxin2/shield

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SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models

https://github.com/lalithbharadwajbaru/wavelet-clip

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Wavelet-Driven Generalizable Framework for Deepfake Face Forgery Detection

https://github.com/langlrsw/AAL-unbiased-authentication

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Additive Adversarial Learning for Unbiased Authentication

https://github.com/lattas/avatarme

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AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"

https://github.com/lava-lab/dynabs

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Robust Control for Dynamical Systems With Non-Gaussian Noise via Formal Abstractions

https://github.com/lava-lab/fba

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Correct-by-construction reach-avoid control of partially observable linear stochastic systems

https://github.com/layer6ai-labs/CAE

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C-Learning: Horizon-Aware Cumulative Accessibility Estimation

https://github.com/leaffeall/DFS-GDD

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Decoupling Forgery Semantics for Generalizable Deepfake Detection

https://github.com/learninginvision/spu

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Self-Paced Deep Regression Forests with Consideration of Ranking Fairness

https://github.com/leebebeto/inter-prototype

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Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children

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