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Video Based Generative Performance 5

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gpt-score

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname
gpt-score
Paper TitleRepository
PPLLaVA-7B3.21PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance-
Video Chat1.94VideoChat: Chat-Centric Video Understanding
VideoChat22.66MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
SlowFast-LLaVA-34B2.77SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
LLaMA Adapter1.98LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
PLLaVA-34B2.67PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
BT-Adapter (zero-shot)2.13BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
Video LLaMA1.82Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
TS-LLaVA-34B2.77TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
MovieChat2.24MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
VTimeLLM2.49VTimeLLM: Empower LLM to Grasp Video Moments
VideoGPT+2.83VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding
Chat-UniVi2.39Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
BT-Adapter2.34BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
ST-LLM2.93ST-LLM: Large Language Models Are Effective Temporal Learners
MiniGPT4-video-7B2.65MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
Video-ChatGPT1.98Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
VideoChat2_HD_mistral2.65MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
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