Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

2

보존된 평가 기록

3

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/toufiksk/darknet

Focal Loss for Dense Object Detection

https://github.com/towhee-io/towhee

Deep Residual Learning for Image Recognition

https://github.com/townim-faisal/Revisiting-Pixel-Wise-Supervision-for-Face-Anti-Spoofing

Revisiting Pixel-Wise Supervision for Face Anti-Spoofing

https://github.com/tphanson/xupr-drl

Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments

https://github.com/trachpro/arcface-tf2

Deep Residual Learning for Image Recognition

https://github.com/trachpro/insightFace_v2

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/trackmania-rl/tmrl

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/travismyers19/Vulnerable_Buildings

Focal Loss for Dense Object Detection

https://github.com/trongnghia00/darknet

Focal Loss for Dense Object Detection

https://github.com/tryolabs/luminoth

Focal Loss for Dense Object Detection

https://github.com/trzy/VGG16

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/tsinghua-rll/gym-gridworld

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/ttruty/facial-feature-mouse-control

Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression

https://github.com/tuanpnm99/RLPongAgent

Proximal Policy Optimization Algorithms

https://github.com/tueboesen/Active-Learning

Cost-Effective Active Learning for Deep Image Classification

https://github.com/tueboesen/a-optimal-active-learning

Cost-Effective Active Learning for Deep Image Classification

https://github.com/tungdt92/GFA-CNN

Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing

https://github.com/tuvovan/Zero_DCE_TF

Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

https://github.com/tuyentv2009/Face-Recognition-

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/twni2016/f-IRL

A Divergence Minimization Perspective on Imitation Learning Methods

https://github.com/twyunting/Deepfake_Video_Classifier

FaceForensics++: Learning to Detect Manipulated Facial Images

https://github.com/u7javed/Image-Enhancer-via-ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/u7javed/Image-Super-Resolution-Enhancer-via-ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/uber-research/ga-world-models

Deep Neuroevolution of Recurrent and Discrete World Models

https://github.com/uclaml/Padam

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/udaya2899/deepfake-detection

Exposing DeepFake Videos By Detecting Face Warping Artifacts

https://github.com/ugail/FaciaIBeautyIEEESKIMA2023

https://github.com/ugo-nama-kun/gym_torcs

Simulated Car Racing Championship: Competition Software Manual

https://github.com/uladzislau-varabei/progressively_growing_gan

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/ultralytics/yolov5

Deep Residual Learning for Image Recognition

https://github.com/umd-fire-coml/2020-Face-Generation

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/umgupta/2d-slice-set-networks

Improved Brain Age Estimation with Slice-based Set Networks

https://github.com/umitkacar/ai-edge-computing

Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

https://github.com/ung200/thats-what-obama-said

ObamaNet: Photo-realistic lip-sync from text

https://github.com/unsky/RetinaNet

Focal Loss for Dense Object Detection

https://github.com/unsky/focal-loss

Focal Loss for Dense Object Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.