Video Based Generative Performance 5

المقاييس

gpt-score

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

		Paper Title
PPLLaVA-7B	3.21	PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance
ST-LLM	2.93	ST-LLM: Large Language Models Are Effective Temporal Learners
VideoGPT+	2.83	VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding
SlowFast-LLaVA-34B	2.77	SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
TS-LLaVA-34B	2.77	TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
PLLaVA-34B	2.67	PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
VideoChat2	2.66	MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
MiniGPT4-video-7B	2.65	MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
VideoChat2_HD_mistral	2.65	MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
VTimeLLM	2.49	VTimeLLM: Empower LLM to Grasp Video Moments
Chat-UniVi	2.39	Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
BT-Adapter	2.34	BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
MovieChat	2.24	MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
BT-Adapter (zero-shot)	2.13	BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
LLaMA Adapter	1.98	LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
Video-ChatGPT	1.98	Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
Video Chat	1.94	VideoChat: Chat-Centric Video Understanding
Video LLaMA	1.82	Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

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Video Based Generative Performance 5 | SOTA | HyperAI