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Generic Event Boundary Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/contentandmaterialportrait/mae-gebd
공식 코드Masked Autoencoders for Generic Event Boundary Detection CVPR'2022 Kinetics-GEBD Challenge
https://github.com/gx77/lcvsl
공식 코드Local Compressed Video Stream Learning for Generic Event Boundary Detection
https://github.com/hello-jinwoo/LOVEU-CVPR2021
공식 코드Winning the CVPR'2021 Kinetics-GEBD Challenge: Contrastive Learning Approach
https://github.com/lufficc/sc-transformer
공식 코드SC-Transformer++: Structured Context Transformer for Generic Event Boundary Detection
https://github.com/mcg-nju/ddm
공식 코드Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection
https://github.com/rayush7/motion_ssl_gebd
공식 코드Motion Aware Self-Supervision for Generic Event Boundary Detection
https://github.com/sming256/timeloc
공식 코드TimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long Videos
https://github.com/th2l/GEBD-PyramidFeatureSimilarity
공식 코드Generic Event Boundary Detection in Video with Pyramid Features
https://github.com/ziwei-zheng/efficientgebd
공식 코드Rethinking the Architecture Design for Efficient Generic Event Boundary Detection
https://github.com/MindSpore-paper-code-3/code2/tree/main/DDM
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection
https://github.com/StanLei52/GEBD
Generic Event Boundary Detection: A Benchmark for Event Segmentation
https://github.com/VisualAnalysisOfHumans/LOVEU_TRACK1_TOP3_SUBMISSION
Generic Event Boundary Detection: A Benchmark for Event Segmentation
https://github.com/code-implementation1/Code1/tree/main/DDM
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.