Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Yang, Yujiu"'
Layout generation is the foundation task of intelligent design, which requires the integration of visual aesthetics and harmonious expression of content delivery. However, existing methods still face challenges in generating precise and visually appe
Externí odkaz:
http://arxiv.org/abs/2407.15233
Autor:
Ji, Yatai, Zhang, Shilong, Wu, Jie, Sun, Peize, Chen, Weifeng, Xiao, Xuefeng, Yang, Sidi, Yang, Yujiu, Luo, Ping
The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities. Nevertheless, current models only focus on the visual content of a single scenario, while their ability to associate instances across
Externí odkaz:
http://arxiv.org/abs/2407.07577
Autor:
Shi, Chufan, Yang, Cheng, Liu, Yaxin, Shui, Bo, Wang, Junjie, Jing, Mohan, Xu, Linran, Zhu, Xinyu, Li, Siheng, Zhang, Yuxiang, Liu, Gongye, Nie, Xiaomei, Cai, Deng, Yang, Yujiu
We introduce a new benchmark, ChartMimic, aimed at assessing the visually-grounded code generation capabilities of large multimodal models (LMMs). ChartMimic utilizes information-intensive visual charts and textual instructions as inputs, requiring L
Externí odkaz:
http://arxiv.org/abs/2406.09961
The newly proposed Generalized Referring Expression Segmentation (GRES) amplifies the formulation of classic RES by involving multiple/non-target scenarios. Recent approaches focus on optimizing the last modality-fused feature which is directly utili
Externí odkaz:
http://arxiv.org/abs/2405.15658
The multimodal deep neural networks, represented by CLIP, have generated rich downstream applications owing to their excellent performance, thus making understanding the decision-making process of CLIP an essential research topic. Due to the complex
Externí odkaz:
http://arxiv.org/abs/2404.08964
Recent advancements have empowered Large Language Models for Vision (vLLMs) to generate detailed perceptual outcomes, including bounding boxes and masks. Nonetheless, there are two constraints that restrict the further application of these vLLMs: the
Externí odkaz:
http://arxiv.org/abs/2404.08506
This paper proposes to correct the rolling shutter (RS) distorted images by estimating the distortion flow from the global shutter (GS) to RS directly. Existing methods usually perform correction using the undistortion flow from the RS to GS. They in
Externí odkaz:
http://arxiv.org/abs/2404.06350
The widespread use of high-definition screens in edge devices, such as end-user cameras, smartphones, and televisions, is spurring a significant demand for image enhancement. Existing enhancement models often optimize for high performance while falli
Externí odkaz:
http://arxiv.org/abs/2403.19238
While Multimodal Large Language Models (MLLMs) have experienced significant advancement in visual understanding and reasoning, their potential to serve as powerful, flexible, interpretable, and text-driven models for Image Quality Assessment (IQA) re
Externí odkaz:
http://arxiv.org/abs/2403.10854
Autor:
Zhang, Xinchen, Yang, Ling, Cai, Yaqi, Yu, Zhaochen, Wang, Kai-Ni, Xie, Jiake, Tian, Ye, Xu, Minkai, Tang, Yong, Yang, Yujiu, Cui, Bin
Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositional generation. In this paper, we propose RealCompo, a new training-fr
Externí odkaz:
http://arxiv.org/abs/2402.12908