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20232026
most citedSmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation

3 citations · 8 across the 15 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026★ 1 cited

Data-Driven Vision-Language Models for Remote Sensing: A Survey

Yue Zhou, Shujun Zhao, Xue Yang +7

During the deep learning era, innovations in remote sensing (RS) vision models primarily focused on optimizing network architectures for specific tasks and conducting end-to-end tr…

cs.CV2026

Let ViT Speak: Generative Language-Image Pre-training

Yan Fang, Mengcheng Lan, Zilong Huang +7

In this paper, we present \textbf{Gen}erative \textbf{L}anguage-\textbf{I}mage \textbf{P}re-training (GenLIP), a minimalist generative pretraining framework for Vision Transformers…

cs.CV2025

Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration

Yue Zhou, Litong Feng, Mengcheng Lan +5

Mathematical reasoning is critical for tasks such as precise distance and area computations, trajectory estimations, and spatial analysis in unmanned aerial vehicle (UAV) based rem…

cs.CV2025

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling

Mengcheng Lan, Chaofeng Chen, Jiaxing Xu +6

Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks. However, effectively integrating image segmentation into these models remains…

cs.CV2024★ 2 cited

GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding

Yue Zhou, Mengcheng Lan, Xiang Li +6

Remote sensing (RS) visual grounding aims to use natural language expression to locate specific objects (in the form of the bounding box or segmentation mask) in RS images, enhanci…

cs.CV2024

Text4Seg: Reimagining Image Segmentation as Text Generation

Mengcheng Lan, Chaofeng Chen, Yue Zhou +5

Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks; however, effectively integrating image segmentation into these models remains…

cs.CV2024

ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation

Mengcheng Lan, Chaofeng Chen, Yiping Ke +3

Open-vocabulary semantic segmentation requires models to effectively integrate visual representations with open-vocabulary semantic labels. While Contrastive Language-Image Pre-tra…

cs.CV2024

ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference

Mengcheng Lan, Chaofeng Chen, Yiping Ke +3

Despite the success of large-scale pretrained Vision-Language Models (VLMs) especially CLIP in various open-vocabulary tasks, their application to semantic segmentation remains cha…

cs.CV2023★ 3 cited

SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation

Mengcheng Lan, Xinjiang Wang, Yiping Ke +3

Unsupervised semantic segmentation is a challenging task that segments images into semantic groups without manual annotation. Prior works have primarily focused on leveraging prior…