258 citations · 530 across the 12 of their papers we have counts for
12 papers · 1 filter
TouchStone: Evaluating Vision-Language Models by Language Models
Shuai Bai, Shusheng Yang, Jinze Bai +6
Large vision-language models (LVLMs) have recently witnessed rapid advancements, exhibiting a remarkable capacity for perceiving, understanding, and processing visual information b…
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Jinze Bai, Shuai Bai, Shusheng Yang +6
In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models (LVLMs) designed to perceive and understand both texts and images. Starting from the Qwen…
ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
Peng Wang, Shijie Wang, Junyang Lin +5
In this work, we explore a scalable way for building a general representation model toward unlimited modalities. We release ONE-PEACE, a highly extensible model with 4B parameters…
OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models
Jinze Bai, Rui Men, Hao Yang +15
Generalist models, which are capable of performing diverse multi-modal tasks in a task-agnostic way within a single model, have been explored recently. Being, hopefully, an alterna…
Pretrained Diffusion Models for Unified Human Motion Synthesis
Jianxin Ma, Shuai Bai, Chang Zhou
Generative modeling of human motion has broad applications in computer animation, virtual reality, and robotics. Conventional approaches develop separate models for different motio…
Single Stage Virtual Try-on via Deformable Attention Flows
Shuai Bai, Huiling Zhou, Zhikang Li +2
Virtual try-on aims to generate a photo-realistic fitting result given an in-shop garment and a reference person image. Existing methods usually build up multi-stage frameworks to…
M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing
Zhikang Li, Huiling Zhou, Shuai Bai +3
The fashion industry has diverse applications in multi-modal image generation and editing. It aims to create a desired high-fidelity image with the multi-modal conditional signal a…
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Peng Wang, An Yang, Rui Men +7
In this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization. We propose OFA, a Task-Agnostic and Mo…
Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
Shuai Bai, Zhedong Zheng, Xiaohan Wang +5
Vehicle search is one basic task for the efficient traffic management in terms of the AI City. Most existing practices focus on the image-based vehicle matching, including vehicle…
Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection
Hanzhe Hu, Shuai Bai, Aoxue Li +2
Conventional deep learning based methods for object detection require a large amount of bounding box annotations for training, which is expensive to obtain such high quality annota…
Class-wise Dynamic Graph Convolution for Semantic Segmentation
Hanzhe Hu, Deyi Ji, Weihao Gan +3
Recent works have made great progress in semantic segmentation by exploiting contextual information in a local or global manner with dilated convolutions, pyramid pooling or self-a…
Multi-hierarchical Independent Correlation Filters for Visual Tracking
Shuai Bai, Zhiqun He, Ting-Bing Xu +3
For visual tracking, most of the traditional correlation filters (CF) based methods suffer from the bottleneck of feature redundancy and lack of motion information. In this paper,…