Papers with Code 아카이브
Video Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 19
- 보존된 평가 기록
- 308
The objective of video retrieval is as follows: given a text query and a pool of candidate videos, select the video which corresponds to the text query. Typically, the videos are returned as a ranked list of candidates and scored via document retrieval metrics.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/thswodnjs3/CSTA
Video Joint Modelling Based on Hierarchical Transformer for Co-summarization
https://github.com/towhee-io/towhee
MDMMT: Multidomain Multimodal Transformer for Video Retrieval
https://github.com/unitaryai/VTC
https://github.com/whwu95/ATM
Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
https://github.com/whwu95/BIKE
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
https://github.com/whwu95/GPT4Vis
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
https://github.com/whwu95/text4vis
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
https://github.com/willard-yuan/video-text-retrieval-papers
MDMMT: Multidomain Multimodal Transformer for Video Retrieval
https://github.com/wqliu657/UniVL
UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
https://github.com/x-plug/mplug
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
https://github.com/x-plug/mplug-owl
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video
https://github.com/xinding-sys/StreamMind
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
https://github.com/yahoo/spivak
https://github.com/yalesong/pvse
Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
https://github.com/yasar-rehman/fedvssl
https://github.com/ycxioooong/MovieSynopsisAssociation
Person Search in Videos with One Portrait Through Visual and Temporal Links
https://github.com/yingsen1/unimd
InternVideo: General Video Foundation Models via Generative and Discriminative Learning
https://github.com/zengyan-97/x-vlm
X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks
https://github.com/zhaoyue-zephyrus/avion
https://github.com/zhihaozhang97/ru-ai
https://github.com/zhoujiahuan1991/cvpr2025-stop
DGL: Dynamic Global-Local Prompt Tuning for Text-Video Retrieval
https://github.com/zhuangshaobin/Video-GPT
https://gitlab.com/grounded-sport-convai/goal-baselines
HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.