HyperAIHyperAI
HomeNewsLatest PapersTutorialsDatasetsWikiSOTALLM ModelsGPU LeaderboardEvents
Search
About
HyperAIHyperAI

Video Question Answering On Msrvtt Qa

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
FrozenBiLM47.0Zero-Shot Video Question Answering via Frozen Bidirectional Language Models-
mPLUG-248.0mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video-
FrozenBiLM (0-shot)16.7Zero-Shot Video Question Answering via Frozen Bidirectional Language Models-
VIOLETv244.5An Empirical Study of End-to-End Video-Language Transformers with Masked Visual Modeling-
Singularity-temporal43.9Revealing Single Frame Bias for Video-and-Language Learning-
HBI46.2Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning-
VALOR49.2VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset-
Singularity43.5Revealing Single Frame Bias for Video-and-Language Learning-
VAST50.1VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset-
Mirasol3B50.42Mirasol3B: A Multimodal Autoregressive model for time-aligned and contextual modalities-
VindLU44.6VindLU: A Recipe for Effective Video-and-Language Pretraining-
COSA49.2COSA: Concatenated Sample Pretrained Vision-Language Foundation Model-
MA-LMM48.5MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding-
EMCL-Net45.8Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations-
0 of 14 row(s) selected.
Video Question Answering On Msrvtt Qa | SOTA | HyperAI