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cs.CV2025

IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning

Quan Zhang, Yuxin Qi, Xi Tang +4

Using extensive training data from SA-1B, the Segment Anything Model (SAM) has demonstrated exceptional generalization and zero-shot capabilities, attracting widespread attention i…

cs.CV2025

Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction

Quan Zhang, Yuxin Qi, Xi Tang +4

Pseudo-label learning methods have been widely applied in weakly-supervised temporal action localization. Existing works directly utilize weakly-supervised base model to generate i…

cs.CV2024

Weakly Supervised Temporal Action Localization via Dual-Prior Collaborative Learning Guided by Multimodal Large Language Models

Quan Zhang, Jinwei Fang, Rui Yuan +4

Recent breakthroughs in Multimodal Large Language Models (MLLMs) have gained significant recognition within the deep learning community, where the fusion of the Video Foundation Mo…

cs.CV2024

Artemis: Towards Referential Understanding in Complex Videos

Jihao Qiu, Yuan Zhang, Xi Tang +6

Videos carry rich visual information including object description, action, interaction, etc., but the existing multimodal large language models (MLLMs) fell short in referential un…

cs.CV2024

ChatterBox: Multi-round Multimodal Referring and Grounding

Yunjie Tian, Tianren Ma, Lingxi Xie +6

In this study, we establish a baseline for a new task named multimodal multi-round referring and grounding (MRG), opening up a promising direction for instance-level multimodal dia…