Video Understanding

VideoLLaMA3: Long Video Understanding with AVT and DiffFP

by
VideoLLaMA3: Long Video Understanding with AVT and DiffFP

Click Follow us with the blue text above Researchers from Alibaba have proposed VideoLLaMA 3, a multimodal foundational model that combines Any-resolution Vision Tokenization (AVT) and Differential Frame Pruner (DiffFP) technologies to effectively handle image and video understanding, achieving significant results in image and video benchmarks, especially excelling in long video understanding and temporal reasoning. … Read more

VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

by
VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding Paper Link: https://arxiv.org/pdf/2501.13106 Abstract 01 In this paper, we propose VideoLLaMA3, a more advanced multimodal foundation model for image and video understanding. The core design philosophy of VideoLLaMA3 is vision-centric, which has two meanings: a vision-centric training paradigm and a vision-centric framework design. The … Read more

Introducing VideoMamba: A Breakthrough in Efficient Video Understanding

by
Introducing VideoMamba: A Breakthrough in Efficient Video Understanding

Machine Heart reports Editor: Rome Rome Video understanding faces immense challenges due to significant spatiotemporal redundancy and complex spatiotemporal dependencies. Overcoming these two issues is extremely difficult, and CNNs, Transformers, and Uniformers struggle to meet these demands. Mamba presents a promising approach; let’s explore how this article creates video understanding with VideoMamba. The core goal … Read more