6 accepted papers
Code language models (LMs) represent valuable intellectual property (IP) as their training involves immense investments, including large-scale code corpora, proprietary annotations, extensive computational resources, and specialized designs. Hence the threat of model IP infringements such as unautho…
Large Vision-Language Models (LVLMs) recently achieve significant breakthroughs in understanding complex visual-textual contexts. However, hallucination issues still limit their real-world applicability. Although previous mitigation methods effectively reduce hallucinations in photographic images, t
Given a natural language query, temporal video grounding aims to localize the described temporal moment in an untrimmed video. A major challenge of this task is its heavy dependence on labor-intensive annotations for training. Unlike existing works that directly train models on manually curated data…
In weakly supervised video anomaly detection, it has been verified that anomalies can be biased by background noise. Previous works attempted to focus on local regions to exclude irrelevant information. However, the abnormal events in different scenes vary in size, and current methods struggle to co…
In recent years, the vulnerability of networks has attracted the attention of researchers. However, in these methods, the impact of video compression coding on the added adversarial perturbation, i.e., the robustness of the video adversarial example, is not considered. When an adversarial sample is…
Detecting double MPEG compression is of prime significance in video forensics. However, existing methods are effective only when the primary compression and the secondary compression have different quantiser scales (QS). There is a lack of effective methods dealing with double MPEG compression with…