https://github.com/alililia/ms_extend/tree/main/gpu_efficientnet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Papers with Code 아카이브
Activity Recognition
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Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.
Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/alinlab/LfF
Learning from Failure: Training Debiased Classifier from Biased Classifier
https://github.com/alirezaghods/Activity2Vec
Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence Model
https://github.com/alles9fresser/Conditional-GAN
https://github.com/alpemek/ais3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/amazon-research/video-contrastive-learning
SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning
https://github.com/amcs1729/Predicting-cloud-CPU-usage-on-Azure-data
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/amira-mira/RA-GCNv22
Richly Activated Graph Convolutional Network for Action Recognition with Incomplete Skeletons
https://github.com/amirdy/dog-breed-classification
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/amyllykoski/CycleGAN
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/anas-r-dev/video-mix-tensorflow
VideoMix: Rethinking Data Augmentation for Video Classification
https://github.com/andresespinosapc/actions-transformations-pytorch
https://github.com/andrewowens/multisensory
Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
https://github.com/anish-lu-yihe/SVRT-by-GAT
https://github.com/ankitshah009/unsupervised_video_retrieval_from_activity
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
https://github.com/anonymous-p/Flickering_Adversarial_Video
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/anonymous0x233/ReuseAndDiffuse
Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation
https://github.com/anskarl/LoMRF
Semi-Supervised Online Structure Learning for Composite Event Recognition
https://github.com/antoine77340/S3D_HowTo100M
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
https://github.com/antoine77340/iccv17learning
Learning from Video and Text via Large-Scale Discriminative Clustering
https://github.com/antoine77340/milnce_howto100m
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
https://github.com/antoninofurnari/rulstm
https://github.com/antoniolq/st-gcn
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/apple/ml-mobileclip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/applecrumble123/CVLR_pytorch
https://github.com/arangoml/fastgraphml
https://github.com/armaank/archlectures
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/armin-azh/3DefficientNet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/arpitsg/CGAN
https://github.com/arturml/mnist-cgan
https://github.com/arundhatikurup/3DResnet
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
https://github.com/arunos728/MotionSqueeze
MotionSqueeze: Neural Motion Feature Learning for Video Understanding
https://github.com/arunos728/arunos728.github.io
IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos
https://github.com/asad-62/IVP-DNN
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/ashikkapadiya/Video-Motion-Retargeting
Learning Character-Agnostic Motion for Motion Retargeting in 2D
https://github.com/ashu5711/Neural_Network_Hand_Gesture_Recognition
Learning Spatiotemporal Features with 3D Convolutional Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.