hshjerry0315/VideoEspresso_train_multi_image

VideoEspresso

This dataset is the multi-image version.

Leaderboard

Model	Params	Frames	Overall	Narrative Analysis	Event Dynamic	Preparation Steps	Causal Analysis	Theme Analysis	Contextual Analysis	Influence Analysis	Role Analysis	Interaction Analysis	Behavior Analysis	Emotion Analysis	Cooking Process	Traffic Analysis	Situation Analysis
LLaVA-Video	72B	64	66.3%	68.4%	66.2%	74.5%	62.7%	62.3%	71.6%	62.5%	63.5%	67.7%	63.2%	60.0%	75.5%	76.7%	74.0%
LLaVA-OneVision	72B	64	63.2%	76.0%	61.8%	71.4%	57.5%	62.3%	68.8%	62.5%	55.6%	58.1%	56.1%	63.1%	77.4%	70.0%	74.0%
InternVL2.5	38B	16	59.9%	65.8%	54.1%	66.3%	57.3%	55.7%	63.3%	56.9%	54.0%	53.2%	63.2%	60.0%	73.6%	70.0%	72.0%
gemini-1.5-pro	-	128	44.2%	55.7%	42.0%	50.0%	41.3%	34.4%	53.2%	29.2%	39.7%	40.3%	38.6%	47.7%	58.5%	50.0%	54.0%
Kangaroo	8B	64	44.1%	41.8%	43.3%	49.0%	42.7%	34.4%	44.0%	61.1%	52.4%	41.9%	33.3%	38.5%	52.8%	53.3%	38.0%
Qwen-Max	-	4	42.7%	44.3%	35.7%	45.9%	39.7%	44.3%	54.1%	43.1%	47.6%	35.5%	45.6%	41.5%	49.1%	46.7%	46.0%
gemini-1.5-flash	-	128	39.8%	59.5%	45.2%	38.8%	34.7%	32.8%	45.9%	30.6%	42.9%	43.6%	33.3%	38.5%	41.5%	36.7%	46.0%
LongVA	7B	128	39.7%	40.5%	33.8%	43.9%	35.9%	42.6%	42.2%	51.4%	47.6%	40.3%	35.1%	32.3%	39.6%	56.7%	48.0%
Qwen-VL-Chat	7B	24	36.2%	49.4%	28.7%	35.7%	32.4%	44.3%	39.5%	47.2%	31.8%	30.7%	40.4%	36.9%	34.0%	43.3%	44.0%
VideoChat2-Mistral	7B	16	32.1%	31.7%	28.7%	27.6%	34.3%	36.1%	27.5%	31.9%	31.8%	43.6%	28.1%	38.5%	20.8%	36.7%	30.0%
Chat-UniVi-v1.5	7B	64	25.5%	24.1%	22.9%	21.4%	24.2%	27.9%	30.3%	30.6%	25.4%	27.4%	22.8%	30.8%	18.9%	36.7%	28.0%
SliME	8B	64	24.8%	19.0%	24.2%	26.5%	27.0%	19.7%	21.1%	30.6%	28.6%	29.0%	19.3%	21.5%	30.2%	20.0%	16.0%
Video-XL	7B	64	24.6%	25.3%	28.0%	22.5%	26.5%	23.0%	21.1%	26.4%	20.6%	27.4%	28.1%	18.5%	13.2%	36.7%	18.0%
Long-LLava	7B	64	13.8%	8.9%	16.6%	19.4%	13.9%	16.4%	12.8%	13.9%	14.3%	12.9%	1.8%	29.2%	7.6%	3.3%	8.0%
ShareGPT4Video	8B	16	8.0%	8.9%	10.8%	12.2%	8.0%	11.5%	8.3%	6.9%	7.9%	8.1%	0.0%	7.7%	3.8%	3.3%	4.0%

Contact Us

If you have any questions or want to submit your checkpoints, feel free to reach out to us via email:

• hshjerry0315@gmail.com
• aaron.weihuang@gmail.com

Citation:

@article{han2024videoespresso,
  title={VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection},
  author={Han, Songhao and Huang, Wei and Shi, Hairong and Zhuo, Le and Su, Xiu and Zhang, Shifeng and Zhou, Xu and Qi, Xiaojuan and Liao, Yue and Liu, Si},
  journal={arXiv preprint arXiv:2411.14794},
  year={2024}
}