https://github.com/DeepSportRadar/ball-3d-localization-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
Papers with Code 아카이브
Sports Understanding
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/deepsportradar/camera-calibration-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
https://github.com/deepsportradar/instance-segmentation-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
https://github.com/deepsportradar/player-reidentification-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
https://github.com/haotianxia/SPORTU
공식 코드SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models
https://github.com/haotianxia/sportqa
공식 코드SportQA: A Benchmark for Sports Understanding in Large Language Models
https://github.com/jyrao/UniSoccer
공식 코드https://github.com/vbursztyn/compositional-fine-tuning
공식 코드Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models
https://github.com/allenai/dolma
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
https://github.com/bramiozo/PubScience
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
https://github.com/karpathy/llama2.c
https://github.com/nkluge-correa/teenytinyllama
https://github.com/open-finance-lab/finlora
https://github.com/rvlopes/gloria
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
https://github.com/yangletliu/finlora
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.