https://github.com/alibaba/AliceMind/tree/main/mPLUG
공식 코드mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
Papers with Code 아카이브
Video Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 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/alibaba/Deep-Vision/tree/main/Context-Motion-Decoupling
공식 코드Self-supervised Video Representation Learning by Context and Motion Decoupling
https://github.com/alipay/Ant-Multi-Modal-Framework
공식 코드Dual-Modal Attention-Enhanced Text-Video Retrieval with Triplet Partial Margin Contrastive Learning
https://github.com/amazon-research/video-contrastive-learning
공식 코드https://github.com/ameenali/videomatch
공식 코드https://github.com/anokiai/contextiq-paper
공식 코드ContextIQ: A Multimodal Expert-Based Video Retrieval System for Contextual Advertising
https://github.com/antoine77340/MIL-NCE_HowTo100M
공식 코드End-to-End Learning of Visual Representations from Uncurated Instructional Videos
https://github.com/antoine77340/Mixture-of-Embedding-Experts
공식 코드Learning a Text-Video Embedding from Incomplete and Heterogeneous Data
https://github.com/antoyang/TubeDETR
공식 코드https://github.com/appletea233/llava-st
공식 코드LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding
https://github.com/appletea233/temporal-r1
공식 코드Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency
https://github.com/aranciokov/fsmmda_videoretrieval
공식 코드A Feature-space Multimodal Data Augmentation Technique for Text-video Retrieval
https://github.com/aranciokov/ranp
공식 코드Learning video retrieval models with relevance-aware online mining
https://github.com/aranciokov/relevancemargin-icmr22
공식 코드Relevance-based Margin for Contrastively-trained Video Retrieval Models
https://github.com/avinashsai/ViRED
공식 코드https://github.com/avinashsai/mml
공식 코드https://github.com/baidu-research/vidpress-sports
공식 코드https://github.com/becomebright/groundvqa
공식 코드https://github.com/bighuang624/vop
공식 코드VoP: Text-Video Co-operative Prompt Tuning for Cross-Modal Retrieval
https://github.com/bingqingzhang/TokenBinder
공식 코드TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm
https://github.com/bladewaltz1/promptswitch
공식 코드Prompt Switch: Efficient CLIP Adaptation for Text-Video Retrieval
https://github.com/bmezaris/texttovideoretrieval-ttimesv
공식 코드https://github.com/bofang98/uatvr
공식 코드https://github.com/bpiyush/TestOfTime
공식 코드Test of Time: Instilling Video-Language Models with a Sense of Time
https://github.com/brian7685/Multimodal-Clustering-Network
공식 코드Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos
https://github.com/bryant1410/fitclip
공식 코드FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks
https://github.com/bryant1410/tclip
공식 코드FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks
https://github.com/buraksatar/RoME_video_retrieval
공식 코드RoME: Role-aware Mixture-of-Expert Transformer for Text-to-Video Retrieval
https://github.com/bytedance/Shot2Story
공식 코드Shot2Story20K: A New Benchmark for Comprehensive Understanding of Multi-shot Videos
https://github.com/bytedance/tarsier
공식 코드https://github.com/callsys/textvr
공식 코드A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension
https://github.com/camma-public/peskavlp
공식 코드Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
https://github.com/camma-public/surgvlp
공식 코드Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
https://github.com/cap-ntu/Video-to-Retail-Platform
공식 코드Hysia: Serving DNN-Based Video-to-Retail Applications in Cloud
https://github.com/caryxiang/eca4vtr
공식 코드Expertized Caption Auto-Enhancement for Video-Text Retrieval
https://github.com/caskcsg/vlp
공식 코드RaP: Redundancy-aware Video-language Pre-training for Text-Video Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.