3 accepted papers
Vision large language models (VLLMs) are focusing primarily on handling complex and fine-grained visual information by incorporating advanced vision encoders and scaling up visual models. However, these approaches face high training and inference costs, as well as challenges in extracting visual det
Although Large Language Models (LLMs) excel in reasoning and generation for language tasks, they are not specifically designed for multimodal challenges. Training Multimodal Large Language Models (MLLMs), however, is resource-intensive and constrained by various training limitations. In this paper,…
With the rapid advancement of object-based video inpainting and splicing tampering techniques, the dissemination of malicious videos on the internet poses significant risks. Existing localization methods, however, exhibit limitations such as restriction to specific datasets, limited performance in d…