https://github.com/rickyHong/tfoptflow-repl
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Papers with Code 아카이브
Action Detection
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- 보존된 평가 기록
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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/rikluost/RL_DQN_Pong
https://github.com/rk1998/robot-sac
https://github.com/rk68657/AutoEncoders
https://github.com/rlaengud123/CMC_LRCN
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/rlleshi/sensor-har
Human Activity Recognition from Wearable Sensor Data Using Self-Attention
https://github.com/romaintha/pytorch_pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/rort1989/HDM
https://github.com/rush-d/spoken-language-identification
https://github.com/ryanchesler/comma-speed-challenge
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/s-sd/task-amenability
https://github.com/saaries/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/sadari1/TumorDetectionDeepLearning
Temporal Convolutional Networks for Action Segmentation and Detection
https://github.com/sair-lab/ni-slam
https://github.com/salmank255/ROADSlowFast
Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization
https://github.com/salmank255/ROAD_Waymo_Baseline
ROAD: The ROad event Awareness Dataset for Autonomous Driving
https://github.com/samiranrl/ODSC_2019_RL
https://github.com/samuelmat19/DDPG-tf2
https://github.com/sanantoniochili/PointCloud_KNN
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/sandman002/One-Style-is-All-You-Need-to-Generate-a-Video
https://github.com/saoudh/Reinforcement-Learning
https://github.com/sarthakTUM/roofn3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/sayantanauddy/hierarchical_bipedal_controller
https://github.com/schatty/D4PG-pytorch
https://github.com/sdimi/cardiofitness
Learning Generalizable Physiological Representations from Large-scale Wearable Data
https://github.com/seanmcgovern21/Machine-Learning-CS539
Online Human Action Detection using Joint Classification-Regression Recurrent Neural Networks
https://github.com/sebastiantiesmeyer/deeplabchop3d
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/secretlyvogon/IndRNNTF
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/secretlyvogon/Neural-Network-Implementations
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/selmiss/gp-tlstgcn
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
https://github.com/ser-art/RAE-vs-AE
https://github.com/seungjaeryanlee/osim-rl-helper
https://github.com/shahabi8/Deep-Reinforcement-Learning
https://github.com/shahin-01/vqa-ad
https://github.com/shakedzy/warehouse
https://github.com/shehrum/RL_Continous-Control
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.