Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Sun, Xiaoshuai"'
Autor:
Wu, Mingrui, Cai, Xinyue, Ji, Jiayi, Li, Jiale, Huang, Oucheng, Luo, Gen, Fei, Hao, Sun, Xiaoshuai, Ji, Rongrong
In this work, we propose a training-free method to inject visual referring into Multimodal Large Language Models (MLLMs) through learnable visual token optimization. We observe the relationship between text prompt tokens and visual tokens in MLLMs, w
Externí odkaz:
http://arxiv.org/abs/2407.21534
Autor:
Wu, Changli, Liu, Yihang, Ji, Jiayi, Ma, Yiwei, Wang, Haowei, Luo, Gen, Ding, Henghui, Sun, Xiaoshuai, Ji, Rongrong
3D Referring Expression Segmentation (3D-RES) is dedicated to segmenting a specific instance within a 3D space based on a natural language description. However, current approaches are limited to segmenting a single target, restricting the versatility
Externí odkaz:
http://arxiv.org/abs/2407.20664
With advancements in data availability and computing resources, Multimodal Large Language Models (MLLMs) have showcased capabilities across various fields. However, the quadratic complexity of the vision encoder in MLLMs constrains the resolution of
Externí odkaz:
http://arxiv.org/abs/2407.16198
Recently, mixture of experts (MoE) has become a popular paradigm for achieving the trade-off between modal capacity and efficiency of multi-modal large language models (MLLMs). Different from previous efforts, we are dedicated to exploring the dynami
Externí odkaz:
http://arxiv.org/abs/2407.14093
3D referring expression comprehension (3DREC) and segmentation (3DRES) have overlapping objectives, indicating their potential for collaboration. However, existing collaborative approaches predominantly depend on the results of one task to make predi
Externí odkaz:
http://arxiv.org/abs/2407.05363
Recently, diffusion models have increasingly demonstrated their capabilities in vision understanding. By leveraging prompt-based learning to construct sentences, these models have shown proficiency in classification and visual grounding tasks. Howeve
Externí odkaz:
http://arxiv.org/abs/2407.05352
The issue of hallucinations is a prevalent concern in existing Large Vision-Language Models (LVLMs). Previous efforts have primarily focused on investigating object hallucinations, which can be easily alleviated by introducing object detectors. Howev
Externí odkaz:
http://arxiv.org/abs/2406.16449
Autor:
Qian, Zhipeng, Zhang, Pei, Yang, Baosong, Fan, Kai, Ma, Yiwei, Wong, Derek F., Sun, Xiaoshuai, Ji, Rongrong
This paper introduces AnyTrans, an all-encompassing framework for the task-Translate AnyText in the Image (TATI), which includes multilingual text translation and text fusion within images. Our framework leverages the strengths of large-scale models,
Externí odkaz:
http://arxiv.org/abs/2406.11432
Text-based person retrieval (TPR) is a challenging task that involves retrieving a specific individual based on a textual description. Despite considerable efforts to bridge the gap between vision and language, the significant differences between the
Externí odkaz:
http://arxiv.org/abs/2406.05620
In this paper, we introduce SemiRES, a semi-supervised framework that effectively leverages a combination of labeled and unlabeled data to perform RES. A significant hurdle in applying semi-supervised techniques to RES is the prevalence of noisy pseu
Externí odkaz:
http://arxiv.org/abs/2406.01451