https://github.com/dairui01/MS-TCT
MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection
Papers with Code 아카이브
Temporal Action Localization
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Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dairui01/PDAN
https://github.com/damien911224/theWorldInSafety
Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/daniansan/i3d_mindspore
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/danielegrattarola/keras-gat
https://github.com/darnbi/pygcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/darrishabh/coviprox
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/MLND_Capstone_Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/malaria-model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/davidpicard/homm
https://github.com/dddb11/MVSS-Net
Image Manipulation Detection by Multi-View Multi-Scale Supervision
https://github.com/debajyotid2/pointnet_pl
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/deepchem/moleculenet
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/deepmind/deepmind-research/tree/master/transporter
Unsupervised Learning of Object Keypoints for Perception and Control
https://github.com/deepmind/kinetics-i3d
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/demianzhang/weakly-action-localization
Weakly Supervised Action Localization by Sparse Temporal Pooling Network
https://github.com/dishen12/py03
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/djwhsdj/vw-sdk
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/dlpbc/keras-kinetics-i3d
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/dmeoli/neuro-sat
https://github.com/dmis-lab/temporalhead
https://github.com/dmlc/dgl/tree/master/examples/mxnet/gat
https://github.com/dmlc/dgl/tree/master/examples/mxnet/gcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/dmlc/dgl/tree/master/examples/mxnet/sgc
https://github.com/dmlc/dgl/tree/master/examples/pytorch/arma
https://github.com/dmlc/dgl/tree/master/examples/pytorch/gat
https://github.com/dmlc/dgl/tree/master/examples/pytorch/sgc
https://github.com/dmlc/dgl/tree/master/examples/tensorflow/gat
https://github.com/dmlc/dgl/tree/master/examples/tensorflow/gcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/dmlc/dgl/tree/master/examples/tensorflow/sgc
https://github.com/donshen/pointnet.phasedetection
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/doronharitan/human_activity_recognition_LRCN
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/dpfried/action-segmentation
Cross-task weakly supervised learning from instructional videos
https://github.com/dreamh1gh/awesome-srl
https://github.com/ds4dm/sGat
https://github.com/ds4dm/sparse-gcn
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.