https://github.com/MindSpore-paper-code-3/code6/tree/main/C3D
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
Papers with Code 아카이브
Activity Detection
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Detecting activities in extended videos.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MuhammadAsadJaved/asad
Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks
https://github.com/PolyuWirelessCommunicationLab/MMV-AMP-with-Side-Information
Exploiting Temporal Side Information in Massive IoT Connectivity
https://github.com/WenwanChen/pvad
https://github.com/dairui01/TSU_evaluation
Toyota Smarthome Untrimmed: Real-World Untrimmed Videos for Activity Detection
https://github.com/idiap/atco2-corpus
https://github.com/ivrit-ai/ivrit.ai
ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development
https://github.com/jwwoody/mlb-deeplearning
https://github.com/jwwoody/mlb-youtube
https://github.com/kyutai-labs/hibiki
Moshi: a speech-text foundation model for real-time dialogue
https://github.com/kyutai-labs/moshivis
Moshi: a speech-text foundation model for real-time dialogue
https://github.com/magahub/mind
An End-to-End Architecture for Keyword Spotting and Voice Activity Detection
https://github.com/mindorii/kws
An End-to-End Architecture for Keyword Spotting and Voice Activity Detection
https://github.com/muskang48/Speaker-Diarization
pyannote.audio: neural building blocks for speaker diarization
https://github.com/pirxus/personalVAD
https://github.com/rush-d/spoken-language-identification
https://github.com/salmank255/ROAD_Waymo_Baseline
ROAD: The ROad event Awareness Dataset for Autonomous Driving
https://github.com/taylorlu/AudioKWS
An End-to-End Architecture for Keyword Spotting and Voice Activity Detection
https://github.com/vohoaiviet/activitynet-2016-cvprw
Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks
https://github.com/wondonghyeon/protest-detection-violence-estimation
Protest Activity Detection and Perceived Violence Estimation from Social Media Images
https://github.com/yurakuratov/hidden_capacity
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.