Computer Science > Computer Vision and Pattern Recognition
arXiv:2406.07476 (cs)
[Submitted on 11 Jun 2024 (v1), last revised 30 Oct 2024 (this version, v3)]
Title:VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
Authors:Zesen Cheng,Sicong Leng,Hang Zhang,Yifei Xin,Xin Li,Guanzheng Chen,Yongxin Zhu,Wenqi Zhang,Ziyang Luo,Deli Zhao,Lidong Bing
View a PDF of the paper titled VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs, by Zesen Cheng and 10 other authors
View PDFHTML (experimental)Abstract:In this paper, we present the VideoLLaMA 2, a set of Video Large Language Models (Video-LLMs) designed to enhance spatial-temporal modeling and audio understanding in video and audio-oriented tasks. Building upon its predecessor, VideoLLaMA 2 incorporates a tailor-made Spatial-Temporal Convolution (STC) connector, which effectively captures the intricate spatial and temporal dynamics of video data. Additionally, we integrate an Audio Branch into the model through joint training, thereby enriching the multimodal understanding capabilities of the model by seamlessly incorporating audio cues. Comprehensive evaluations on multiple-choice video question answering (MC-VQA), open-ended video question answering (OE-VQA), and video captioning (VC) tasks demonstrate that VideoLLaMA 2 consistently achieves competitive results among open-source models and even gets close to some proprietary models on several benchmarks. Furthermore, VideoLLaMA 2 exhibits reasonable improvements in audio-only and audio-video question-answering (AQA & OE-AVQA) benchmarks over existing models. These advancements underline VideoLLaMA 2's superior performance in multimodal comprehension, setting a new standard for intelligent video analysis systems. All models are public to facilitate further research.
| Comments: | ZC, SL, HZ, YX, and XL contributed equally to this project. Code:this https URL |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Computation and Language (cs.CL) |
| Cite as: | arXiv:2406.07476 [cs.CV] |
| (orarXiv:2406.07476v3 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2406.07476 arXiv-issued DOI via DataCite |
Submission history
From: Sicong Leng [view email][v1] Tue, 11 Jun 2024 17:22:23 UTC (1,813 KB)
[v2] Mon, 17 Jun 2024 16:40:43 UTC (1,815 KB)
[v3] Wed, 30 Oct 2024 06:49:54 UTC (1,821 KB)
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View a PDF of the paper titled VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs, by Zesen Cheng and 10 other authors
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