Papers with Code 아카이브

Action Detection

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하위 태스크: 8
평가표: 11
보존된 평가 기록: 81

Action Detection aims to find both where and when an action occurs within a video clip and classify what the action is taking place. Typically results are given in the form of action tublets, which are action bounding boxes linked across time in the video. This is related to temporal localization, which seeks to identify the start and end frame of an action, and action recognition, which seeks only to classify which action is taking place and typically assumes a trimmed video.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/marblet/gat-pytorch

Graph Attention Networks

https://github.com/marload/DeepRL-TensorFlow2

Continuous control with deep reinforcement learning

https://github.com/massquantity/DBRL

Continuous control with deep reinforcement learning

https://github.com/mathformoso/RL-playground---ddpg

Continuous control with deep reinforcement learning

https://github.com/matthewsparr/Reinforcement-Learning-Lesson

Continuous control with deep reinforcement learning

https://github.com/maxstrobel/HCN-PrototypeLoss-PyTorch

Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation

https://github.com/mcgridles/LENS

UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

https://github.com/mdeff/paper-cnn-graph-nips2016

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

https://github.com/meliketoy/graph-cnn.pytorch

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/memory-attention-networks/MANs

Memory Attention Networks for Skeleton-based Action Recognition

https://github.com/mengxingshifen1218/pointnet.pytorch

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/merazlab/3D_Deep_Learning_Link

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/metalbubble/moments_models

Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding

https://github.com/microsoft/qlib/tree/main/examples/benchmarks/ADARNN

AdaRNN: Adaptive Learning and Forecasting of Time Series

https://github.com/miladvazan/LDA-MLP-SVM-SGD

https://github.com/mindorii/kws

An End-to-End Architecture for Keyword Spotting and Voice Activity Detection

https://github.com/mindspore-ai/models/tree/master/official/gnn/gat

Graph Attention Networks

https://github.com/mindspore-courses/Deep-Reinforcement-Learning-Algorithms-with-MindSpore

Continuous control with deep reinforcement learning

https://github.com/minhncedutw/pointnet1_keras

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/mitya8128/experiments_notes

Graph Attention Networks

https://github.com/mlzxzhou/keras-gnm

Graph Attention Networks

https://github.com/mmalekzadeh/motion-sense

DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data

https://github.com/montaserFath/Reinforcement-Learning-for-Prosthetics

Continuous control with deep reinforcement learning

https://github.com/mpuu00001/Siformer

Siformer: Feature-isolated Transformer for Efficient Skeleton-based Sign Language Recognition

https://github.com/muskang48/Speaker-Diarization

pyannote.audio: neural building blocks for speaker diarization

https://github.com/mustafa1728/TA3N-Lightning

Rescaling Egocentric Vision

https://github.com/mzolfaghari/chained-multistream-networks

Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection

https://github.com/nassimmokhtari/Enhanced-Spatio-Temporal-Image-Encoding

https://github.com/nassimmokhtari/Spatio-Temporal-Image-Encoding

https://github.com/natepuppy/HCN-pytorch

Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation

https://github.com/nav74neet/ddpg4biped

Continuous control with deep reinforcement learning

https://github.com/nav74neet/ddpg_biped

Continuous control with deep reinforcement learning

https://github.com/nav74neet/rl4biped

Continuous control with deep reinforcement learning

https://github.com/nddoshi/pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/negarhdr/PGCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/neilsong/slt

Skeleton Aware Multi-modal Sign Language Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.