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Text to Video Retrieval

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 75 papers

TitleStatusHype
X-Pool: Cross-Modal Language-Video Attention for Text-Video RetrievalCode1
FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding TasksCode0
Revitalize Region Feature for Democratizing Video-Language Pre-training of RetrievalCode1
MDMMT-2: Multidomain Multimodal Transformer for Video Retrieval, One More Step Towards Generalization—0
Reading-strategy Inspired Visual Representation Learning for Text-to-Video RetrievalCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video RetrievalCode1
VIOLET : End-to-End Video-Language Transformers with Masked Visual-token ModelingCode1
Advancing High-Resolution Video-Language Representation with Large-Scale Video TranscriptionsCode1
VALUE: A Multi-Task Benchmark for Video-and-Language Understanding EvaluationCode1
DeCEMBERT: Learning from Noisy Instructional Videos via Dense Captions and Entropy MinimizationCode1
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled VideosCode1
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and TextCode1
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip RetrievalCode1
CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning—0
Frozen in Time: A Joint Video and Image Encoder for End-to-End RetrievalCode1
MDMMT: Multidomain Multimodal Transformer for Video RetrievalCode1
Less is More: ClipBERT for Video-and-Language Learning via Sparse SamplingCode1
Support-set bottlenecks for video-text representation learning—0
The End-of-End-to-End: A Video Understanding Pentathlon Challenge (2020)Code1
Retrieving and Highlighting Action with Spatiotemporal Reference—0
Condensed Movies: Story Based Retrieval with Contextual EmbeddingsCode1
Noise Estimation Using Density Estimation for Self-Supervised Multimodal LearningCode0
End-to-End Learning of Visual Representations from Uncurated Instructional VideosCode1
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video ClipsCode1
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All datasetsKinetics-GEB+MSR-VTTMSVD-Indonesian

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FROZEN-revisedmAP23.39—Unverified
2FROZEN-revised (two-stream)text-to-video R@112.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP4Cliptext-to-video R@144.5—Unverified
#ModelMetricClaimedVerifiedStatus
1X-CLIP (Cross-Lingual)R@132.3—Unverified