172 citations · 199 across the 16 of their papers we have counts for
8 papers · 1 filter
Segment and Caption Anything
Xiaoke Huang, Jianfeng Wang, Yansong Tang +5
We propose a method to efficiently equip the Segment Anything Model (SAM) with the ability to generate regional captions. SAM presents strong generalizability to segment anything w…
MM-Narrator: Narrating Long-form Videos with Multimodal In-Context Learning
Chaoyi Zhang, Kevin Lin, Zhengyuan Yang +5
We present MM-Narrator, a novel system leveraging GPT-4 with multimodal in-context learning for the generation of audio descriptions (AD). Unlike previous methods that primarily fo…
GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation
An Yan, Zhengyuan Yang, Wanrong Zhu +9
We present MM-Navigator, a GPT-4V-based agent for the smartphone graphical user interface (GUI) navigation task. MM-Navigator can interact with a smartphone screen as human users,…
OpenLEAF: Open-Domain Interleaved Image-Text Generation and Evaluation
Jie An, Zhengyuan Yang, Linjie Li +5
This work investigates a challenging task named open-domain interleaved image-text generation, which generates interleaved texts and images following an input query. We propose a n…
MM-VID: Advancing Video Understanding with GPT-4V(ision)
Kevin Lin, Faisal Ahmed, Linjie Li +9
We present MM-VID, an integrated system that harnesses the capabilities of GPT-4V, combined with specialized tools in vision, audio, and speech, to facilitate advanced video unders…
The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)
Zhengyuan Yang, Linjie Li, Kevin Lin +4
Large multimodal models (LMMs) extend large language models (LLMs) with multi-sensory skills, such as visual understanding, to achieve stronger generic intelligence. In this paper,…
Idea2Img: Iterative Self-Refinement with GPT-4V(ision) for Automatic Image Design and Generation
Zhengyuan Yang, Jianfeng Wang, Linjie Li +4
We introduce ``Idea to Image,'' a system that enables multimodal iterative self-refinement with GPT-4V(ision) for automatic image design and generation. Humans can quickly identify…
Completing Visual Objects via Bridging Generation and Segmentation
Xiang Li, Yinpeng Chen, Chung-Ching Lin +6
This paper presents a novel approach to object completion, with the primary goal of reconstructing a complete object from its partially visible components. Our method, named MaskCo…