Papers with Code 아카이브

Text to Video Retrieval

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하위 태스크: 1
평가표: 3
보존된 평가 기록: 4

She's gone I can't find her anywhere I'm looking everywhere for her Everywhere is dark

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ArrowLuo/CLIP4Clip

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CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval

https://github.com/GenjiB/ECLIPSE

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ECLIPSE: Efficient Long-range Video Retrieval using Sight and Sound

https://github.com/HuiGuanLab/ms-sl

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Partially Relevant Video Retrieval

https://github.com/Maddy12/MultiModalVideoRobustness/tree/master/code

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Robustness Analysis of Video-Language Models Against Visual and Language Perturbations

https://github.com/VALUE-Leaderboard/StarterCode

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VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation

https://github.com/WACV2025Submission/ContextIQ

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ContextIQ: A Multimodal Expert-Based Video Retrieval System for Contextual Advertising

https://github.com/adxcreative/EERCF

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Towards Efficient and Effective Text-to-Video Retrieval with Coarse-to-Fine Visual Representation Learning

https://github.com/anokiai/contextiq-paper

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ContextIQ: A Multimodal Expert-Based Video Retrieval System for Contextual Advertising

https://github.com/antoine77340/MIL-NCE_HowTo100M

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End-to-End Learning of Visual Representations from Uncurated Instructional Videos

https://github.com/avinashsai/ViRED

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Learning to Retrieve Videos by Asking Questions

https://github.com/bmezaris/texttovideoretrieval-ttimesv

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Are All Combinations Equal? Combining Textual and Visual Features with Multiple Space Learning for Text-Based Video Retrieval

https://github.com/brian7685/Multimodal-Clustering-Network

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Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos

https://github.com/bryant1410/fitclip

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FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks

https://github.com/bryant1410/tclip

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FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks

https://github.com/buraksatar/RoME_video_retrieval

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RoME: Role-aware Mixture-of-Expert Transformer for Text-to-Video Retrieval

https://github.com/cuthbertcai/demovlp

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Revitalize Region Feature for Democratizing Video-Language Pre-training of Retrieval

https://github.com/elad-amrani/ssml

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Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning

https://github.com/google-research/google-research/tree/master/vatt

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VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text

https://github.com/hritikbansal/videocon

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VideoCon: Robust Video-Language Alignment via Contrast Captions

https://github.com/huangmozhi9527/GMMFormer

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GMMFormer: Gaussian-Mixture-Model Based Transformer for Efficient Partially Relevant Video Retrieval

https://github.com/huangmozhi9527/gmmformer_v2

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GMMFormer v2: An Uncertainty-aware Framework for Partially Relevant Video Retrieval

https://github.com/jasoncodemaker/ctvr

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StableFusion: Continual Video Retrieval via Frame Adaptation

https://github.com/jayleicn/ClipBERT

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Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling

https://github.com/jayleicn/singularity

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Revealing Single Frame Bias for Video-and-Language Learning

https://github.com/jingxiaolun/tc-mgc

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TC-MGC: Text-Conditioned Multi-Grained Contrastive Learning for Text-Video Retrieval

https://github.com/klauscc/vindlu

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VindLU: A Recipe for Effective Video-and-Language Pretraining

https://github.com/layer6ai-labs/xpool

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X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval

https://github.com/leeyn-43/clover

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Clover: Towards A Unified Video-Language Alignment and Fusion Model

https://github.com/leolee99/pau

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Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval

https://github.com/lijiabei-7/rivrl

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Reading-strategy Inspired Visual Representation Learning for Text-to-Video Retrieval

https://github.com/m-bain/frozen-in-time

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Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval

https://github.com/microsoft/lavender

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LAVENDER: Unifying Video-Language Understanding as Masked Language Modeling

https://github.com/microsoft/xpretrain

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Advancing High-Resolution Video-Language Representation with Large-Scale Video Transcriptions

https://github.com/mlvlab/MELTR

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MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models

https://github.com/papermsucode/mdmmt

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MDMMT: Multidomain Multimodal Transformer for Video Retrieval

https://github.com/ruc-aimc-lab/laff

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Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval

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