https://github.com/guoshengcv/cacl
공식 코드Cross-Architecture Self-supervised Video Representation Learning
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/gxym/stgt
공식 코드Video-Language Alignment via Spatio-Temporal Graph Transformer
https://github.com/hazeld/action-modifiers
공식 코드Action Modifiers: Learning from Adverbs in Instructional Videos
https://github.com/hazeld/pseudoadverbs
공식 코드How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs
https://github.com/hdy007007/prem
공식 코드Improving Video Corpus Moment Retrieval with Partial Relevance Enhancement
https://github.com/henglan/cgstvg
공식 코드https://github.com/houzhijian/cone
공식 코드CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding
https://github.com/houzhijian/conquer
공식 코드CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval
https://github.com/hqqasw/person-search-PPCC
공식 코드Person Search in Videos with One Portrait Through Visual and Temporal Links
https://github.com/hritikbansal/videocon
공식 코드VideoCon: Robust Video-Language Alignment via Contrast Captions
https://github.com/hrtang22/MUSE
공식 코드MUSE: Mamba is Efficient Multi-scale Learner for Text-video Retrieval
https://github.com/huangb23/vtimellm
공식 코드https://github.com/huangmozhi9527/GMMFormer
공식 코드GMMFormer: Gaussian-Mixture-Model Based Transformer for Efficient Partially Relevant Video Retrieval
https://github.com/huangmozhi9527/conmh
공식 코드Contrastive Masked Autoencoders for Self-Supervised Video Hashing
https://github.com/huangmozhi9527/gmmformer_v2
공식 코드GMMFormer v2: An Uncertainty-aware Framework for Partially Relevant Video Retrieval
https://github.com/hyeon-jo/PSPNet
공식 코드Self-Supervised Visual Learning by Variable Playback Speeds Prediction of a Video
https://github.com/iigroup/scl
공식 코드Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning
https://github.com/intel/TVP
공식 코드Text-Visual Prompting for Efficient 2D Temporal Video Grounding
https://github.com/intellabs/multimodal_cognitive_ai
공식 코드ICSVR: Investigating Compositional and Syntactic Understanding in Video Retrieval Models
https://github.com/invictus717/MiCo
공식 코드https://github.com/ioanacroi/qb-norm
공식 코드https://github.com/ispamm/GRAM
공식 코드https://github.com/j-min/HiREST
공식 코드https://github.com/jasoncodemaker/ctvr
공식 코드StableFusion: Continual Video Retrieval via Frame Adaptation
https://github.com/jayaprakash-a/Cross-Modal-learning-for-Audio-Visual-Video-Parsing
공식 코드https://github.com/jayleicn/ClipBERT
공식 코드Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling
https://github.com/jayleicn/TVCaption
공식 코드TVR: A Large-Scale Dataset for Video-Subtitle Moment Retrieval
https://github.com/jayleicn/TVRetrieval
공식 코드TVR: A Large-Scale Dataset for Video-Subtitle Moment Retrieval
https://github.com/jayleicn/singularity
공식 코드https://github.com/jellyyao3000/omnistvg
공식 코드OmniSTVG: Toward Spatio-Temporal Omni-Object Video Grounding
https://github.com/jerryyli/svitt
공식 코드https://github.com/jiawangbai/DHTA-master
공식 코드https://github.com/jingxiaolun/tc-mgc
공식 코드TC-MGC: Text-Conditioned Multi-Grained Contrastive Learning for Text-Video Retrieval
https://github.com/jinhyunj/eatr
공식 코드Knowing Where to Focus: Event-aware Transformer for Video Grounding
https://github.com/jpthu17/HBI
공식 코드Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning
https://github.com/jpthu17/dicosa
공식 코드Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.