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Zero Shot Video Question Answer On Tvqa

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Accuracy
Paper TitleRepository
VideoChat2 (no speech)40.6MVBench: A Comprehensive Multi-modal Video Understanding Benchmark-
FrozenBiLM (with speech)59.7Zero-Shot Video Question Answering via Frozen Bidirectional Language Models-
FrozenBILM (no speech)29.7Zero-Shot Video Question Answering via Frozen Bidirectional Language Models-
InternVideo (no speech)35.9InternVideo: General Video Foundation Models via Generative and Discriminative Learning-
IG-VLM (no speech, GPT-4V)57.8An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM-
VideoChat_HD_mistral (no speech)50.6MVBench: A Comprehensive Multi-modal Video Understanding Benchmark-
VideoChat_mistral (no speech)46.4MVBench: A Comprehensive Multi-modal Video Understanding Benchmark-
SEVILA (no speech)38.2Self-Chained Image-Language Model for Video Localization and Question Answering-
MiniGPT4-video-7B54.21MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens-
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Zero Shot Video Question Answer On Tvqa | SOTA | HyperAI