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20212024
most citedFlorence: A New Foundation Model for Computer Vision

342 citations · 1.2k across the 36 of their papers we have counts for

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Showing 2023Show all

16 papers · 1 filter

cs.CV2023

InfoVisDial: An Informative Visual Dialogue Dataset by Bridging Large Multimodal and Language Models

Bingbing Wen, Zhengyuan Yang, Jianfeng Wang +3

In this paper, we build a visual dialogue dataset, named InfoVisDial, which provides rich informative answers in each round even with external knowledge related to the visual conte…

cs.CV2023

Interfacing Foundation Models' Embeddings

Xueyan Zou, Linjie Li, Jianfeng Wang +10

Foundation models possess strong capabilities in reasoning and memorizing across modalities. To further unleash the power of foundation models, we present FIND, a generalized inter…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023★ 10 cited

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,…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 10 cited

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…

cs.CV2023★ 1 cited

DEsignBench: Exploring and Benchmarking DALL-E 3 for Imagining Visual Design

Kevin Lin, Zhengyuan Yang, Linjie Li +2

We introduce DEsignBench, a text-to-image (T2I) generation benchmark tailored for visual design scenarios. Recent T2I models like DALL-E 3 and others, have demonstrated remarkable…

cs.CV2023★ 172 cited

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,…

cs.CV2023★ 2 cited

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…

cs.AI2023★ 59 cited

MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Weihao Yu, Zhengyuan Yang, Linjie Li +5

We propose MM-Vet, an evaluation benchmark that examines large multimodal models (LMMs) on complicated multimodal tasks. Recent LMMs have shown various intriguing abilities, such a…

cs.CV2023★ 2 cited

Spatial-Frequency U-Net for Denoising Diffusion Probabilistic Models

Xin Yuan, Linjie Li, Jianfeng Wang +4

In this paper, we study the denoising diffusion probabilistic model (DDPM) in wavelet space, instead of pixel space, for visual synthesis. Considering the wavelet transform represe…

cs.CV2023★ 24 cited

Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Fuxiao Liu, Kevin Lin, Linjie Li +3

Despite the promising progress in multi-modal tasks, current large multi-modal models (LMMs) are prone to hallucinating inconsistent descriptions with respect to the associated ima…

cs.CV2023★ 1 cited

NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation

Shengming Yin, Chenfei Wu, Huan Yang +13

In this paper, we propose NUWA-XL, a novel Diffusion over Diffusion architecture for eXtremely Long video generation. Most current work generates long videos segment by segment seq…

cs.CV2023★ 80 cited

MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Zhengyuan Yang, Linjie Li, Jianfeng Wang +7

We propose MM-REACT, a system paradigm that integrates ChatGPT with a pool of vision experts to achieve multimodal reasoning and action. In this paper, we define and explore a comp…

cs.CV2023

Learning 3D Photography Videos via Self-supervised Diffusion on Single Images

Xiaodong Wang, Chenfei Wu, Shengming Yin +9

3D photography renders a static image into a video with appealing 3D visual effects. Existing approaches typically first conduct monocular depth estimation, then render the input f…