Video LMMs

Video Large Multimodal Models (Video-LMMs) aim to enable computers to understand and reason about video content, bridging the gap between visual data and natural language processing. Current research focuses on improving video quality assessment, extending the processing capabilities of these models to longer videos, and developing more efficient architectures like MLP-based approaches. This field is crucial for advancing video understanding tasks across diverse applications, from improving video compression and generation to enabling more sophisticated AI assistants and autonomous systems. The development of comprehensive benchmarks is also a key focus, highlighting the need for robust evaluation of Video-LMMs' reasoning and robustness in complex scenarios.