52 citations · 83 across the 21 of their papers we have counts for
7 papers · 1 filter
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…
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…
Multi-Atlas Brain Network Classification through Consistency Distillation and Complementary Information Fusion
Jiaxing Xu, Mengcheng Lan, Xia Dong +4
In the realm of neuroscience, identifying distinctive patterns associated with neurological disorders via brain networks is crucial. Resting-state functional magnetic resonance ima…
Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification
Jiaxing Xu, Kai He, Mengcheng Lan +5
Understanding neurological disorder is a fundamental problem in neuroscience, which often requires the analysis of brain networks derived from functional magnetic resonance imaging…
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…
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…
Towards Vision-Language Geo-Foundation Model: A Survey
Yue Zhou, Zhihang Zhong, Litong Feng +4
Vision-Language Foundation Models (VLFMs) have made remarkable progress on various multimodal tasks, such as image captioning, image-text retrieval, visual question answering, and…