Papers with Code 아카이브

3D Face Modelling

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평가표

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보존된 평가 기록

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코드

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

https://github.com/astoff/dog-breed-app

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/astoycos/Mini_Project2

Deep Residual Learning for Image Recognition

https://github.com/atom06/Tiny_Faces_in_Tensorflow_v2

Can we still avoid automatic face detection?

https://github.com/audio-df-ucb/clonedvoicedetection

WaveFake: A Data Set to Facilitate Audio Deepfake Detection

https://github.com/aurelien-peden/Deep-Learning-paper-implementations

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/automl/learna

Proximal Policy Optimization Algorithms

https://github.com/autonomobil/SCDND-P2_Traffic-Sign-Classifier

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/autonomousvision/frequency_bias

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

https://github.com/autumnwu/aggressive-q-learning-with-ensembles

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

https://github.com/av-savchenko/emotiefflib

Frame-level Prediction of Facial Expressions, Valence, Arousal and Action Units for Mobile Devices

https://github.com/aviralkumar2907/BEAR

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction

https://github.com/aviros/pointnet_totations

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/aviros/roatationPointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/avishai111/One-Class-Learning-with-Adaptive-Centroid-Shift-for-Audio-Deepfake-Detection

One-Class Learning with Adaptive Centroid Shift for Audio Deepfake Detection

https://github.com/avivelor/UnityMachineLearningForProjectButterfly

Continuous control with deep reinforcement learning

https://github.com/avocardio/resnet_vs_convnext

Deep Residual Learning for Image Recognition

https://github.com/avuku06/G

A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing

https://github.com/axium/Blind-Image-Deconvolution-using-Deep-Generative-Priors

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

https://github.com/axmoyal/Steganalysis-with-CNN

Deep Residual Learning for Image Recognition

https://github.com/axnedergaard/normalized-advantage-functions

Continuous Deep Q-Learning with Model-based Acceleration

https://github.com/ayushdabra/drone-images-semantic-segmentation

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/ayushdabra/lunar-landscape-images-segmentation

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/ayushdabra/retinal-oct-images-classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/ayushgupta9198/gan

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/ayushgupta9198/stylegan

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/ayushpalak/darknet_cokebottles

Focal Loss for Dense Object Detection

https://github.com/ayushpalak/darknet_multi_cokebottles

Focal Loss for Dense Object Detection

https://github.com/azshue/TPT

Learning to Prompt for Vision-Language Models

https://github.com/b06b01073/Twin-Delayed-DDPG

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/b06b01073/continuous-control

Continuous control with deep reinforcement learning

https://github.com/b5071/pulse-rev

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/b8goal/PIRL-Residual-network

Deep Residual Learning for Image Recognition

https://github.com/bacdavid/HER

Continuous control with deep reinforcement learning

https://github.com/backgom2357/Recommender_system_via_deep_RL

Continuous control with deep reinforcement learning

https://github.com/bailvwangzi/repulsion_loss_ssd

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/bakerv/fer-webcam

Facial Emotion Recognition: State of the Art Performance on FER2013

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