https://github.com/CellSMB/EM-net
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
3D Face Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CenIII/WSNet
https://github.com/Chang-Chia-Chi/TrackNet-Badminton-Tracking-tensorflow2
https://github.com/ChangweiZhang/Awesome-WindowsML-ONNX-Models
https://github.com/CharlesPikachu/CharlesFace
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/CharlotteMorrison/Baxter-Research
Addressing Function Approximation Error in Actor-Critic Methods
https://github.com/CharlotteMorrison/Baxter-VREP
Addressing Function Approximation Error in Actor-Critic Methods
https://github.com/CharlotteMorrison/Baxter-VREP-Version-2
Addressing Function Approximation Error in Actor-Critic Methods
https://github.com/CheesyB/cpointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ChiCheng123/SRN
Selective Refinement Network for High Performance Face Detection
https://github.com/ChristianMarzahl/ObjectDetection
https://github.com/Christopheraburns/openai-gym
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
https://github.com/ChristosKap/policy_consolidation
https://github.com/Cloud-Computing-IoT/Cloud-Enabled-Smart-Speaker
https://github.com/Cloud-Computing-IoT/speakEasy
https://github.com/Cmeijiang/PointNet_MS
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/CocoSungMin/Gachon_SW_Colorization_Contest
https://github.com/CodeChefVIT/VOID
https://github.com/CoinCheung/pytorch-loss
Partial FC: Training 10 Million Identities on a Single Machine
https://github.com/CompVis/metric-learning-divide-and-conquer
https://github.com/CompVis/unsupervised-part-segmentation
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/Conero007/Emotion-Detection-Pytorch
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/CorentinMAG/SRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/CorneliusHsiao/FoodMethodGAN
https://github.com/Crevass/Hybrid-Agent
https://github.com/CrossEntropy/Gesture-images-recognition-ResidualNetwork
https://github.com/CryptoSalamander/pytorch_paper_implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/CycloneBoy/PPDetectionPytorch
https://github.com/D-X-Y/ResNeXt-DenseNet
https://github.com/DChaushev/Age-Gender-Recognition
https://github.com/DELTA37/LatentKeypointGAN
https://github.com/DHDev0/Muzero-unplugged
Online and Offline Reinforcement Learning by Planning with a Learned Model
https://github.com/DILiS-lab/drivers-of-predictive-aleatoric-uncertainty
FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild
https://github.com/DInesh1234-wq/tyredataset
https://github.com/DMIU-ShELL/MOSAIC
https://github.com/DMarwan/NutricIA
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.