Papers with Code 아카이브
Egocentric Activity Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ekazakos/temporal-binding-network
공식 코드EPIC-Fusion: Audio-Visual Temporal Binding for Egocentric Action Recognition
https://github.com/facebookresearch/Ego-Exo
공식 코드Ego-Exo: Transferring Visual Representations from Third-person to First-person Videos
https://github.com/facebookresearch/lavila
공식 코드https://github.com/facebookresearch/video-long-term-feature-banks
공식 코드https://github.com/fpv-iplab/rulstm
공식 코드https://github.com/haoyanbin918/group-contextualization
공식 코드https://github.com/kylemin/Gaze-Attention
공식 코드Integrating Human Gaze into Attention for Egocentric Activity Recognition
https://github.com/mariusbock/wear
공식 코드WEAR: An Outdoor Sports Dataset for Wearable and Egocentric Activity Recognition
https://github.com/swathikirans/LSTA
공식 코드LSTA: Long Short-Term Attention for Egocentric Action Recognition
https://github.com/swathikirans/ego-rnn
공식 코드Attention is All We Need: Nailing Down Object-centric Attention for Egocentric Activity Recognition
https://github.com/BoChenUIUC/YOWO
https://github.com/Ziyang412/VideoTree
https://github.com/antoninofurnari/rulstm
https://github.com/ceezh/llovi
https://github.com/guiggh/hand_pose_action
First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
https://github.com/microsoft/computervision-recipes
Large-scale weakly-supervised pre-training for video action recognition
https://github.com/moabitcoin/ig65m-pytorch
Large-scale weakly-supervised pre-training for video action recognition
https://github.com/open-mmlab/mmaction2
https://github.com/rkahani/FirstPersonActivityRecognition
A Correlation Based Feature Representation for First-Person Activity Recognition
https://github.com/wei-tim/YOWO
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.