Accueil Actualités Articles de recherche récents Tutoriels Ensembles de données Wiki SOTA Modèles LLM Classement GPU Événements

Français

Zero Shot Video Question Answer On Intentqa

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	Paper Title	Repository
IG-VLM	65.3	An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM	-
VideoTree (GPT4)	66.9	VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos	-
VidCtx (7B)	67.1	VidCtx: Context-aware Video Question Answering with Image Models	-
LLoVi (GPT-4)	64.0	A Simple LLM Framework for Long-Range Video Question-Answering	-
LangRepo (12B)	59.1	Language Repository for Long Video Understanding	-
SeViLA (4B)	60.9	Self-Chained Image-Language Model for Video Localization and Question Answering	-
LVNet	71.1	Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA	-
ENTER	71.5	ENTER: Event Based Interpretable Reasoning for VideoQA	-
LLoVi (7B)	53.6	A Simple LLM Framework for Long-Range Video Question-Answering	-
Mistral (7B)	50.4	Mistral 7B	-
TS-LLaVA-34B	67.9	TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models	-
SlowFast-LLaVA-34B	60.1	SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models	-
Random	20.0	-	-

0 of 13 row(s) selected.

Zero Shot Video Question Answer On Intentqa | SOTA | HyperAI