https://github.com/ArminS03/CAREL
공식 코드CAREL: Instruction-guided reinforcement learning with cross-modal auxiliary objectives
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/ArrowLuo/CLIP4Clip
공식 코드CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
https://github.com/Aveek-Saha/VIRALIQ
공식 코드https://github.com/BestJuly/Inter-intra-video-contrastive-learning
공식 코드Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework
https://github.com/BestJuly/Pretext-Contrastive-Learning
공식 코드Pretext-Contrastive Learning: Toward Good Practices in Self-supervised Video Representation Leaning
https://github.com/CryhanFang/CLIP2Video
공식 코드https://github.com/DavidZhang73/AssemblyVideoManualAlignment
공식 코드Aligning Step-by-Step Instructional Diagrams to Video Demonstrations
https://github.com/Deferf/CLIP_Video_Representation
공식 코드https://github.com/ExplainableML/ReGaDa
공식 코드Video-adverb retrieval with compositional adverb-action embeddings
https://github.com/FangyunWei/SLRT
공식 코드CiCo: Domain-Aware Sign Language Retrieval via Cross-Lingual Contrastive Learning
https://github.com/GenjiB/ECLIPSE
공식 코드ECLIPSE: Efficient Long-range Video Retrieval using Sight and Sound
https://github.com/Guaranteer/VidSTG-Dataset
공식 코드Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences
https://github.com/HJYao00/Side4Video
공식 코드Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
https://github.com/HengLan/TA-STVG
공식 코드Knowing Your Target: Target-Aware Transformer Makes Better Spatio-Temporal Video Grounding
https://github.com/HopLee6/VJMHT-PyTorch
공식 코드Video Joint Modelling Based on Hierarchical Transformer for Co-summarization
https://github.com/HuiGuanLab/ms-sl
공식 코드https://github.com/MKLab-ITI/visil
공식 코드ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
https://github.com/Maddy12/MultiModalVideoRobustness/tree/master/code
공식 코드Robustness Analysis of Video-Language Models Against Visual and Language Perturbations
https://github.com/Paranioar/UniPT
공식 코드UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory
https://github.com/ParitoshParmar/Win-Fail-Action-Recognition
공식 코드https://github.com/PeihaoChen/RSPNet
공식 코드RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning
https://github.com/Roc-Ng/HANet
공식 코드HANet: Hierarchical Alignment Networks for Video-Text Retrieval
https://github.com/SCZwangxiao/RTQ-MM2023
공식 코드RTQ: Rethinking Video-language Understanding Based on Image-text Model
https://github.com/SUTDCV/Animal-Kingdom
공식 코드Animal Kingdom: A Large and Diverse Dataset for Animal Behavior Understanding
https://github.com/SichengMo/Ego4D_NLQ_Actionformer
공식 코드A Simple Transformer-Based Model for Ego4D Natural Language Queries Challenge
https://github.com/TXH-mercury/VALOR
공식 코드VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
https://github.com/TengdaHan/CoCLR
공식 코드Self-supervised Co-training for Video Representation Learning
https://github.com/TengdaHan/MemDPC
공식 코드Memory-augmented Dense Predictive Coding for Video Representation Learning
https://github.com/VALUE-Leaderboard/StarterCode
공식 코드VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
https://github.com/WACV2025Submission/ContextIQ
공식 코드ContextIQ: A Multimodal Expert-Based Video Retrieval System for Contextual Advertising
https://github.com/XinshaoAmosWang/Improving-Mean-Absolute-Error-against-CCE
공식 코드https://github.com/YichengDuan/svrllm
공식 코드Enhancing Subsequent Video Retrieval via Vision-Language Models (VLMs)
https://github.com/adrianofragomeni/contra
공식 코드ConTra: (Con)text (Tra)nsformer for Cross-Modal Video Retrieval
https://github.com/adxcreative/EERCF
공식 코드https://github.com/albanie/collaborative-experts
공식 코드TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval
https://github.com/alibaba/AliceMind
공식 코드mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.