Zeroshot Video Question Answer On Activitynet

Métriques

Accuracy

Confidence Score

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	Confidence Score	Paper Title	Repository
MovieChat	45.7	3.1	MovieChat: From Dense Token to Sparse Memory for Long Video Understanding	-
BT-Adapter (zero-shot)	46.1	3.2	BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning	-
Tarsier (34B)	61.6	3.7	Tarsier: Recipes for Training and Evaluating Large Video Description Models	-
VideoChat2	49.1	3.3	MVBench: A Comprehensive Multi-modal Video Understanding Benchmark	-
Chat-UniVi	46.1	3.3	Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding	-
LLaMA-VID-13B (2 Token)	47.5	3.3	LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models	-
PLLaVA (34B)	60.9	3.7	PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning	-
IG-VLM	58.4	3.5	An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM	-
SlowFast-LLaVA-34B	59.2	3.5	SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models	-
LLaVA-Mini	53.5	3.5	LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token	-
FrozenBiLM	24.7	-	Zero-Shot Video Question Answering via Frozen Bidirectional Language Models	-
Video Chat	26.5	2.2	VideoChat: Chat-Centric Video Understanding	-
LLaMA-VID-7B (2 Token)	47.4	3.3	LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models	-
Video-ChatGPT	35.2	2.7	Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models	-
Flash-VStream	51.9	3.4	Flash-VStream: Memory-Based Real-Time Understanding for Long Video Streams	-
Video-LLaVA	45.3	3.3	Video-LLaVA: Learning United Visual Representation by Alignment Before Projection	-
TS-LLaVA-34B	58.9	3.5	TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models	-
Elysium	43.4	2.9	Elysium: Exploring Object-level Perception in Videos via MLLM	-
PPLLaVA-7B	60.7	3.6	PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance	-
LinVT-Qwen2-VL(7B)	60.1	3.6	LinVT: Empower Your Image-level Large Language Model to Understand Videos	-

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