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/ModelBunker/PointNet-TensorFlow

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

https://github.com/Moon-Xuezha/PointNet

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

https://github.com/MrSyee/pg-is-all-you-need

Continuous control with deep reinforcement learning

https://github.com/MuhammadAsadJaved/asad

Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks

https://github.com/NEUdeep/MOC-Detector-Pytorch1.4

Actions as Moving Points

https://github.com/NOHYC/autonomous_driving_car_project

Continuous control with deep reinforcement learning

https://github.com/NVIDIA/flownet2-pytorch

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

https://github.com/NVlabs/STEP

STEP: Spatio-Temporal Progressive Learning for Video Action Detection

https://github.com/Negus25/GAT-Mindspore

Graph Attention Networks

https://github.com/NervanaSystems/coach

Continuous control with deep reinforcement learning

https://github.com/OanaIgnat/i3d_keras

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/Ontheway361/BSN_pytorch

BSN: Boundary Sensitive Network for Temporal Action Proposal Generation

https://github.com/PPPrior/i3d-pytorch

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/PaParaZz1/PointNet

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

https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/localization/bmn.md

BMN: Boundary-Matching Network for Temporal Action Proposal Generation

https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/slowfast.md

SlowFast Networks for Video Recognition

https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/stgcn.md

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/PaddlePaddle/models/tree/develop/PaddleCV/video/models/bsn

BSN: Boundary Sensitive Network for Temporal Action Proposal Generation

https://github.com/PaddlePaddle/models/tree/develop/dygraph/bmn

BMN: Boundary-Matching Network for Temporal Action Proposal Generation

https://github.com/Parapompadoo/Temporal_Action_Detection

A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning

https://github.com/Pathakvishnu/Human-Activity-Recognition-

Human Activity Recognition with Convolutional Neural Netowrks

https://github.com/Pechckin/MountainCar

Continuous control with deep reinforcement learning

https://github.com/Peihao-Xiang/Label-Ranker

https://github.com/PeterJochem/Deep_RL

Continuous control with deep reinforcement learning

https://github.com/PeterJochem/Double_Deep_QLearning

Continuous control with deep reinforcement learning

https://github.com/Philori22/DDPG-aigym

Continuous control with deep reinforcement learning

https://github.com/Phimos/Paddle-PointNet

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

https://github.com/PolyuWirelessCommunicationLab/MMV-AMP-with-Side-Information

Exploiting Temporal Side Information in Massive IoT Connectivity

https://github.com/Powercoder64/TAA-GCN

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/PumpkinYing/GAT

Graph Attention Networks

https://github.com/Remtasya/DDPG-Actor-Critic-Reinforcement-Learning-Reacher-Environment

Continuous control with deep reinforcement learning

https://github.com/SBPL-Cruz/perch_pose_sampler

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

https://github.com/SY-Xuan/pointnet_paddle

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

https://github.com/SaminYeasar/off_policy_ac

Continuous control with deep reinforcement learning

https://github.com/SergiPonsa/Reinforcement-Learning-Sergi

Continuous control with deep reinforcement learning

https://github.com/ShadowShadowWong/update-pointnet-work

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

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