most citedVL-Mamba: Exploring State Space Models for Multimodal Learning

10 citations · 11 across the 3 of their papers we have counts for

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cs.CV2026

UniFixer: A Universal Reference-Guided Fixer for Diffusion-Based View Synthesis

Sihan Chen, Xiang Zhang, Yang Zhang +2

With the recent surge of generative models, diffusion-based approaches have become mainstream for view synthesis tasks, either in an explicit depth-warp-inpaint or in an implicit e…

cs.CV2024

Fuse & Calibrate: A bi-directional Vision-Language Guided Framework for Referring Image Segmentation

Yichen Yan, Xingjian He, Sihan Chen +2

Referring Image Segmentation (RIS) aims to segment an object described in natural language from an image, with the main challenge being a text-to-pixel correlation. Previous method…

cs.CV20241 cited

Calibration & Reconstruction: Deep Integrated Language for Referring Image Segmentation

Yichen Yan, Xingjian He, Sihan Chen +1

Referring image segmentation aims to segment an object referred to by natural language expression from an image. The primary challenge lies in the efficient propagation of fine-gra…

cs.CV202410 cited

VL-Mamba: Exploring State Space Models for Multimodal Learning

Yanyuan Qiao, Zheng Yu, Longteng Guo +5

Multimodal large language models (MLLMs) have attracted widespread interest and have rich applications. However, the inherent attention mechanism in its Transformer structure requi…

cs.CV2023

EAVL: Explicitly Align Vision and Language for Referring Image Segmentation

Yichen Yan, Xingjian He, Wenxuan Wang +2

Referring image segmentation (RIS) aims to segment an object mentioned in natural language from an image. The main challenge is text-to-pixel fine-grained correlation. In the previ…