1 citations · 1 across the 2 of their papers we have counts for
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MG-LLaVA: Towards Multi-Granularity Visual Instruction Tuning
Xiangyu Zhao, Xiangtai Li, Haodong Duan +4
Multi-modal large language models (MLLMs) have made significant strides in various visual understanding tasks. However, the majority of these models are constrained to process low-…
Auto Cherry-Picker: Learning from High-quality Generative Data Driven by Language
Yicheng Chen, Xiangtai Li, Yining Li +4
Diffusion models can generate realistic and diverse images, potentially facilitating data availability for data-intensive perception tasks. However, leveraging these models to boos…
MotionBooth: Motion-Aware Customized Text-to-Video Generation
Jianzong Wu, Xiangtai Li, Yanhong Zeng +5
In this work, we present MotionBooth, an innovative framework designed for animating customized subjects with precise control over both object and camera movements. By leveraging a…
OMG-Seg: Is One Model Good Enough For All Segmentation?
Xiangtai Li, Haobo Yuan, Wei Li +6
In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models. We propose OMG-Seg, One Model that is Good enough to effici…
RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
Shilin Xu, Haobo Yuan, Qingyu Shi +9
Recent segmentation methods, which adopt large-scale data training and transformer architecture, aim to create one foundation model that can perform multiple tasks. However, most o…
Towards Language-Driven Video Inpainting via Multimodal Large Language Models
Jianzong Wu, Xiangtai Li, Chenyang Si +8
We introduce a new task -- language-driven video inpainting, which uses natural language instructions to guide the inpainting process. This approach overcomes the limitations of tr…