The first video Chain-of-Thought reasoning framework, VoT, which decomposes raw complex problems into a chain of sub-problems, and reasons through multiple steps from low to high levels, enabling not only pixel perceptive recognition …

2024年7月12日 · 视频思维链VoT让视频多模态大 语言模型 在复杂视频的理解和推理性能上大幅提升。 该工作已被ICML 2024录用为Oral paper。 相比于理解和推理静态的图片，在视觉处理社区，推理视频的难度要复杂困难很多，因为视频天然地存在更具挑战的动态时序特性，以及存在更多冗余的视觉内容。 过去的视频理解研究多集中于视频的浅层 感知，如 视频动作识别 、动态识别和视频描述生成。 然而，这些方法对复杂视频的深入理解和推理仍存在显著不足。 相较于浅层 …

VoT inherits the Chain-of-Thought (CoT) core, breaking down a complex task into simpler and manageable sub-problems, and addressing them step-by-step from a low-level pixel perception to high-level cognitive interpretation.

5 天之前 · In the field of video-language pretraining, existing models face numerous challenges in terms of inference efficiency and multimodal data processing. This paper proposes a KunLunBaize-VoT-R1 video inference model based on a long-sequence image encoder, along with its training and application methods. By integrating image packing technology, the Autonomy-of-Experts (AoE) architecture, and ...

2024年7月19日 · 视频思维链VoT让视频多模态大语言模型在复杂视频的理解和推理性能上大幅提升。 该工作已被ICML 2024录用为Oral paper。 论文标题： Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition 论文链接： https://openreview.net/pdf?id=fO31YAyNbI 项目链接： http://haofei.vip/VoT/

2024年7月30日 · 最近，一项名为Video-of-Thought（VoT）的新型视频思维链推理框架被提出，它有望在视频理解领域带来重大突破。 VoT由来自加州大学伯克利分校和Facebook AI Research（FAIR）的研究人员共同开发，旨在建立一个能够像人类一样从感知到认知全面推理视 …

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This is the repository of the project homepage: ICML 2024, Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition. Visit here: VoT. This work is licensed under a …

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