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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Silver-L/OctConv
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://github.com/SilviaLauraPintea/DejaVu
https://github.com/SilvioGiancola/SoccerNet-code
SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
https://github.com/SilvioGiancola/SoccerNetv2-DevKit
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
https://github.com/SimoneDutto/EDSR
https://github.com/Singh07-Shubham/pytorch-object-detection
https://github.com/SiskonEmilia/StyleGAN-PyTorch
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/Sjunna9819/My-First-Project
https://github.com/SmartPorridge/google-AVA-Dataset-downloader
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
https://github.com/Soldelli/VLG-Net
VLG-Net: Video-Language Graph Matching Network for Video Grounding
https://github.com/Soldie/DeOldify-colorir-imagens-antigas
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/SonginCV/GMPHD_MAF
https://github.com/SonginCV/GMPHD_SAF
https://github.com/SonginCV/MAF_HDA
https://github.com/SonuDileep/3-D-Object-Detection-using-PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/SpikeKing/VQA-v2
https://github.com/Spoorthy-gunda/Image-Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/StanfordHCI/virtualhome
https://github.com/StanfordVL/RubiksNet
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/StanfordVL/roboturk_real_dataset
https://github.com/StefOe/indrnn-pytorch
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/StevRamos/video_summarization
Supervised Video Summarization via Multiple Feature Sets with Parallel Attention
https://github.com/Subrata11/IoT-based-Real-time-Human-Motion-Recognition-Based-on-Skeletons-
https://github.com/Sun1992/SSTCN-for-SLR
https://github.com/SunnyHaze/ManTraNet-Pytorch
https://github.com/Sunnydreamrain/IndRNN
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/Superlee506/Correlation_Filtering_Tracking_Lib
https://github.com/SupratimH/neural-style-transfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Sushmitha-Katti/DepthModel
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/SuyashSonawane/fakedetector
https://github.com/Sy-Zhang/Geometric-Feature-Release
https://github.com/Sy-Zhang/MMC-PCFG
Learning a Grammar Inducer from Massive Uncurated Instructional Videos
https://github.com/SysCV/qd-3dt
https://github.com/T-a-g-z/Yotube-VOS-OVS
https://github.com/TAMU-VITA/Privacy-AdversarialLearning
Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.