Video Question Answering on MSRVTT-MC

Metric: Accuracy (higher is better)

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	VIOLETv2	97.6	No	An Empirical Study of End-to-End Video-Language ...	2022-09-04	Code
2	HiTeA	97.4	No	HiTeA: Hierarchical Temporal-Aware Video-Languag...	2022-12-30	-
3	VindLU	95.5	No	VindLU: A Recipe for Effective Video-and-Languag...	2022-12-09	Code
4	Clover	95.2	No	Clover: Towards A Unified Video-Language Alignme...	2022-07-16	Code
5	Singularity-temporal	93.7	No	Revealing Single Frame Bias for Video-and-Langua...	2022-06-07	Code
6	Norton	92.7	No	Multi-granularity Correspondence Learning from L...	2024-01-30	Code
7	Singularity	92.1	No	Revealing Single Frame Bias for Video-and-Langua...	2022-06-07	Code

#1VIOLETv2SOTA
97.6
Accuracy· 2022-09-04
An Empirical Study of End-to-End Video-Language Transformers with Masked Visual Modeling Code
#2HiTeA
97.4
Accuracy· 2022-12-30
HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training
#3VindLU
95.5
Accuracy· 2022-12-09
VindLU: A Recipe for Effective Video-and-Language Pretraining Code
#4CloverSOTA
95.2
Accuracy· 2022-07-16
Clover: Towards A Unified Video-Language Alignment and Fusion Model Code
#5Singularity-temporalSOTA
93.7
Accuracy· 2022-06-07
Revealing Single Frame Bias for Video-and-Language Learning Code
#6Norton
92.7
Accuracy· 2024-01-30
Multi-granularity Correspondence Learning from Long-term Noisy Videos Code
#7Singularity
92.1
Accuracy· 2022-06-07
Revealing Single Frame Bias for Video-and-Language Learning Code