https://github.com/kyutai-labs/hibiki
Moshi: a speech-text foundation model for real-time dialogue
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/kyutai-labs/moshivis
Moshi: a speech-text foundation model for real-time dialogue
https://github.com/l13025816/PGCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/lab-midas/lapnet
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
https://github.com/labmlai/annotated_deep_learning_paper_implementations
https://github.com/lauradhatt/Interesting-Reads
Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos
https://github.com/liampetti/DDPG
https://github.com/lingzhang1/pointnet_pytorch
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/lingzhang1/pointnet_tensorflow
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/lipingcoding/pygcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/liu6zijian/simplified-gcn-model
https://github.com/liuch37/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/liujf69/TD-GCN-Gesture
https://github.com/liupengyuan/EmotionAction_EmotionInference
Emotion Action Detection and Emotion Inference: the Task and Dataset
https://github.com/liuyuezhang/pyrl
https://github.com/lmnt-com/haste
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/luke-bhan/TwitterSentimentAnalysisTool
https://github.com/lukebhan/TwitterSentimentAnalysisTool
https://github.com/lukecavabarrett/pna
https://github.com/m-117/PointNet-ein-Implementationsbeispiel-mit-Jupyter-Notebooks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/mHealthBuet/SegCodeNet
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/madhur-tandon/RL-Project
https://github.com/madvn/DDPG
https://github.com/magahub/mind
An End-to-End Architecture for Keyword Spotting and Voice Activity Detection
https://github.com/maggie0106/Graph-CNN-in-3D-Point-Cloud-Classification
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/magnux/DMNN
https://github.com/mahendrathapa/graph-convolution-network
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/mahequn001/graphlearning/tree/master/model_zoo/gcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/mahsa91/GKD
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/mahsa91/RA-GCN
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/majercakdavid/gym-virtual-quant-trading
https://github.com/manish-vi/Human-Activity-Recognition
Understanding and Improving Deep Neural Network for Activity Recognition
https://github.com/manu-vishwakarma/human-activity-detection
Understanding and Improving Deep Neural Network for Activity Recognition
https://github.com/marble0117/GNN_models_pytorch
https://github.com/marble0117/GNN_models_pytorch_geometric
https://github.com/marblet/GNN_models_pytorch_geometric
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.