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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/Richard-61/FineAction

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FineAction: A Fine-Grained Video Dataset for Temporal Action Localization

https://github.com/Rxannro/SWL-Adapt

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SWL-Adapt: An Unsupervised Domain Adaptation Model with Sample Weight Learning for Cross-User Wearable Human Activity Recognition

https://github.com/SPEECHCOG/data2vec_maiju

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Evaluation of self-supervised pre-training for automatic infant movement classification using wearable movement sensors

https://github.com/Siyu-C/ACAR-Net

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Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization

https://github.com/StrohmayerJ/wallhack1.8k

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Data Augmentation Techniques for Cross-Domain WiFi CSI-based Human Activity Recognition

https://github.com/Sunnydreamrain/IndRNN_Theano_Lasagne

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Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

https://github.com/Sunnydreamrain/IndRNN_pytorch

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Deep Independently Recurrent Neural Network (IndRNN)

https://github.com/TaeSoo-Kim/TCNActionRecognition

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Interpretable 3D Human Action Analysis with Temporal Convolutional Networks

https://github.com/TaoRuijie/TalkNet_ASD

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Is Someone Speaking? Exploring Long-term Temporal Features for Audio-visual Active Speaker Detection

https://github.com/Tiiiger/SGC

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Simplifying Graph Convolutional Networks

https://github.com/Uason-Chen/CTR-GCN

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Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

https://github.com/VITA-Group/21LPCV-UAV-Solution

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E^2TAD: An Energy-Efficient Tracking-based Action Detector

https://github.com/Va6lue/BST-Badminton-Stroke-type-Transformer

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BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports

https://github.com/VisionLearningGroup/R-C3D

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R-C3D: Region Convolutional 3D Network for Temporal Activity Detection

https://github.com/Walter0807/MotionBERT

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MotionBERT: A Unified Perspective on Learning Human Motion Representations

https://github.com/Whiffe/Custom-ava-dataset_Custom-Spatio-Temporally-Action-Video-Dataset

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A Multi-Person Video Dataset Annotation Method of Spatio-Temporally Actions

https://github.com/Xu-Linfeng/UESTC_MMEA_CL_main

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Towards Continual Egocentric Activity Recognition: A Multi-modal Egocentric Activity Dataset for Continual Learning

https://github.com/YangDi666/UNIK

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UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition

https://github.com/YinxPeng/HA-CM-main

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Spatial Hierarchy and Temporal Attention Guided Cross Masking for Self-supervised Skeleton-based Action Recognition

https://github.com/ZhenyueQin/Angular-Skeleton-Encoding

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Fusing Higher-order Features in Graph Neural Networks for Skeleton-based Action Recognition

https://github.com/ZhouYuxuanYX/Hypergraph-Transformer-for-Skeleton-based-Action-Recognition

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Hypergraph Transformer for Skeleton-based Action Recognition

https://github.com/ZichenMiao/GNN-with-Low-rank-Learnable-Local-Filters

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Graph Convolution with Low-rank Learnable Local Filters

https://github.com/ZichenMiao/L3Net

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Graph Convolution with Low-rank Learnable Local Filters

https://github.com/ZikangLeng/IMUGPT

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Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition

https://github.com/ZiweiXU/CapsuleMotion

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Unsupervised Motion Representation Learning with Capsule Autoencoders

https://github.com/aaai-24/generative-based-kd

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Generative Model-based Feature Knowledge Distillation for Action Recognition

https://github.com/aakiraotok/yowov3

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YOWOv3: An Efficient and Generalized Framework for Human Action Detection and Recognition

https://github.com/aau-es-ml/VAD-with-adversarial-multi-task-learning

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Adversarial Multi-Task Deep Learning for Noise-Robust Voice Activity Detection with Low Algorithmic Delay

https://github.com/aayushjr/ssa2d

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We don't Need Thousand Proposals$\colon$ Single Shot Actor-Action Detection in Videos

https://github.com/abduallahmohamed/har-gcnn

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HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data

https://github.com/adeboissiere/FUSION-human-action-recognition

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Infrared and 3D skeleton feature fusion for RGB-D action recognition

https://github.com/againerju/tcg_recognition

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Traffic Control Gesture Recognition for Autonomous Vehicles

https://github.com/ahoelzemann/annotationmatters

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A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors

https://github.com/ahoelzemann/hangtime_har

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Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensors

https://github.com/aikuniverse/tcte-net

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Temporal-Channel Topology Enhanced Network for Skeleton-Based Action Recognition

https://github.com/aimagelab/STAGE_action_detection

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Video action detection by learning graph-based spatio-temporal interactions

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