2 citations · 2 across the 13 of their papers we have counts for
12 papers · 1 filter
PACE-Mem: Prefix-Aware Complementary Evidence for Multimodal Agents
Shidu Ren, Rong-cheng Tu, Hang Zhou +1
As multimodal agents accumulate experience, their long-term memories contain many similar observations of recurring scenes, actions, and entities. Answer quality depends on the evi…
SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense
Siyuan Liang, Yupeng Qiu, Junfeng Fang +3
Text-to-Video (T2V) generative models are vulnerable to jailbreak attacks in real-world deployment, leading them to produce harmful or inappropriate content. Existing defense appro…
AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization
Jingyi Liao, Yongyi Su, Rong-Cheng Tu +6
While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly detection (AD) remains constrain…
SPAZER: Spatial-Semantic Progressive Reasoning Agent for Zero-shot 3D Visual Grounding
Zhao Jin, Rong-Cheng Tu, Jingyi Liao +4
3D Visual Grounding (3DVG) aims to localize target objects within a 3D scene based on natural language queries. To alleviate the reliance on costly 3D training data, recent studies…
Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval
Rong-Cheng Tu, Wenhao Sun, Hanzhe You +4
Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve target images given a compositional query, consisting of a reference image and a modifying text-without relying on anno…
MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval
Rong-Cheng Tu, Zhao Jin, Jingyi Liao +4
Existing Zero-Shot Composed Image Retrieval (ZS-CIR) methods typically train adapters that convert reference images into pseudo-text tokens, which are concatenated with the modifyi…
VORTA: Efficient Video Diffusion via Routing Sparse Attention
Wenhao Sun, Rong-Cheng Tu, Yifu Ding +4
Video diffusion transformers have achieved remarkable progress in high-quality video generation, but remain computationally expensive due to the quadratic complexity of attention o…
Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift
Jingyi Liao, Xun Xu, Yongyi Su +4
Anomaly detection plays a crucial role in quality control for industrial applications. However, ensuring robustness under unseen domain shifts such as lighting variations or sensor…
AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
Wenhao Sun, Rong-Cheng Tu, Jingyi Liao +2
Diffusion Transformers (DiTs) have proven effective in generating high-quality videos but are hindered by high computational costs. Existing video DiT sampling acceleration methods…
SPAgent: Adaptive Task Decomposition and Model Selection for General Video Generation and Editing
Rong-Cheng Tu, Wenhao Sun, Zhao Jin +3
While open-source video generation and editing models have made significant progress, individual models are typically limited to specific tasks, failing to meet the diverse needs o…
Diffusion Model-Based Video Editing: A Survey
Wenhao Sun, Rong-Cheng Tu, Jingyi Liao +1
The rapid development of diffusion models (DMs) has significantly advanced image and video applications, making "what you want is what you see" a reality. Among these, video editin…
A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models
Xincheng Shuai, Henghui Ding, Xingjun Ma +3
Image editing aims to edit the given synthetic or real image to meet the specific requirements from users. It is widely studied in recent years as a promising and challenging field…