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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/YiruS/pointnet_adversarial
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Yonder-OSS/D3M-Primitives
https://github.com/Young98CN/pointconv_pytorch
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Ysp9714/SlowFastNet-keras
https://github.com/Yuki0114/UndergraduateThesis_SRCNN_keras
https://github.com/YunjiKim/Unsupervised-Keypoint-Learning-for-Guiding-Class-conditional-Video-Prediction
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
https://github.com/YunseobShin/wiki_GAT
https://github.com/Yuto0107/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/YvanG/VQGAN-CLIP
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/ZC119/richardson_tracking
https://github.com/ZJCV/Non-local
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/ZJCV/TSN
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/ZJCV/X3D
X3D: Expanding Architectures for Efficient Video Recognition
https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/fairmot.py
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/i3d.py
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/r2plus1d.py
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/ZQPei/deep_sort_pytorch
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/ZTao-z/multiflow-resnet-ssd
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ZacharyGoshen/cifar-10-classifier
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Zasder3/Tganv2-PyTorch-Train-Sparsely--Generate-Densely
https://github.com/Ze-Yang/Context-Transformer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ZeinabRahbar/Implementation-for-the-paper-of-SEMI-SUPERVISED-CLASSIFICATION-WITH-GRAPH-CONVOLUTIONAL-NETWORKS
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/Zhachory1/MusicNST
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ZhangNYG/BSN
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
https://github.com/ZhangNYG/ST-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/ZhangwenguangHikvision/YoloV5_JDE_TensorRT_for_Track
Simple Online and Realtime Tracking with a Deep Association Metric
https://github.com/Zhangyanbo/iResNetLab
https://github.com/ZhaoHengrun/EDVR
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/ZhengChang467/MAU
https://github.com/ZhiHanZ/IRIS0-SPAN
https://github.com/ZhihaoZhu/PointNet-Implementation-Tensorflow
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ZiyiLiubird/GRIP_Plus_Plus
GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving
https://github.com/Zoky-2020/Set-level_Guidance_Attack
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/ZurMaD/RRIN
https://github.com/a-doering/tracker_w_correlation_motion_model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.