Video-based Generative Performance Benchmarking (Contextual Understanding)
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Benchmarks
VideoInstruct
Most implemented
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
Papers
TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
Recent advances in multimodal Large Language Models (LLMs) have shown great success in understanding multi-modal contents. For video understanding tasks, training-based video LLMs are difficult to build due to the scarci…
MVBenchVideo-based Generative Performance BenchmarkingVideo-based Generative Performance Benchmarking (Consistency)Video-based Generative Performance Benchmarking (Contextual Understanding)+5PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance
The past year has witnessed the significant advancement of video-based large language models. However, the challenge of developing a unified model for both short and long video understanding remains unresolved. Most exis…
Caption GenerationMultiple-choiceVideo-based Generative Performance BenchmarkingVideo-based Generative Performance Benchmarking (Consistency)+7SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
We propose SlowFast-LLaVA (or SF-LLaVA for short), a training-free video large language model (LLM) that can jointly capture detailed spatial semantics and long-range temporal context without exceeding the token budget o…
Language ModelingLanguage ModellingLarge Language Model+8VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding
Building on the advances of language models, Large Multimodal Models (LMMs) have contributed significant improvements in video understanding. While the current video LMMs utilize advanced Large Language Models (LLMs), th…
Dense Video CaptioningMVBenchQuestion AnsweringVCGBench-Diverse+10PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
Vision-language pre-training has significantly elevated performance across a wide range of image-language applications. Yet, the pre-training process for video-related tasks demands exceptionally large computational and …
Dense CaptioningMVBenchVideo-based Generative Performance BenchmarkingVideo-based Generative Performance Benchmarking (Consistency)+7MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
This paper introduces MiniGPT4-Video, a multimodal Large Language Model (LLM) designed specifically for video understanding. The model is capable of processing both temporal visual and textual data, making it adept at un…
Language ModelingLanguage ModellingLarge Language ModelMultimodal Large Language Model+10