https://github.com/tanveer81/revisionllm
RGNet: A Unified Clip Retrieval and Grounding Network for Long Videos
Papers with Code 아카이브
Video-Text Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 4
Video-Text retrieval requires understanding of both video and language together. Therefore it's different to video retrieval task.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/towhee-io/towhee
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
https://github.com/unitaryai/VTC
https://github.com/willard-yuan/video-text-retrieval-papers
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
https://github.com/x-plug/mplug
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
https://github.com/xinding-sys/StreamMind
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
https://github.com/yalesong/pvse
Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
https://github.com/zhaoyue-zephyrus/avion
https://github.com/zhihaozhang97/ru-ai
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.