https://github.com/rlaengud123/CMC_LRCN
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Action Localization is finding the spatial and temporal co ordinates for an action in a video. An action localization model will identify which frame an action start and ends in video and return the x,y coordinates of an action. Further the co ordinates will change when the object performing action undergoes a displacement.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
Very Deep Convolutional Networks for Large-Scale Image Recognition
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips
Very Deep Convolutional Networks for Large-Scale Image Recognition
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Temporal Convolutional Networks for Action Segmentation and Detection
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
Very Deep Convolutional Networks for Large-Scale Image Recognition
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
Proposal-Free Temporal Action Detection via Global Segmentation Mask Learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
A Deep Multi-Modal Cyber-Attack Detection in Industrial Control Systems
Very Deep Convolutional Networks for Large-Scale Image Recognition
Online Human Action Detection using Joint Classification-Regression Recurrent Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.