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20232025
most citedSkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery

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

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cs.CV2025

Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation

Inclusion AI, :, Bowen Ma +73

We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which on…

cs.CV2025

ARGenSeg: Image Segmentation with Autoregressive Image Generation Model

Xiaolong Wang, Lixiang Ru, Ziyuan Huang +4

We propose a novel AutoRegressive Generation-based paradigm for image Segmentation (ARGenSeg), achieving multimodal understanding and pixel-level perception within a unified framew…

cs.CV2025

CasP: Improving Semi-Dense Feature Matching Pipeline Leveraging Cascaded Correspondence Priors for Guidance

Peiqi Chen, Lei Yu, Yi Wan +9

Semi-dense feature matching methods have shown strong performance in challenging scenarios. However, the existing pipeline relies on a global search across the entire feature map t…

cs.CV2025

SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing

Yingying Zhang, Lixiang Ru, Kang Wu +4

The multi-modal remote sensing foundation model (MM-RSFM) has significantly advanced various Earth observation tasks, such as urban planning, environmental monitoring, and natural…

cs.CV2025

Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction

Inclusion AI, Biao Gong, Cheng Zou +14

We introduce Ming-Lite-Uni, an open-source multimodal framework featuring a newly designed unified visual generator and a native multimodal autoregressive model tailored for unifyi…

cs.CV2025

Cross-View Geo-Localization with Street-View and VHR Satellite Imagery in Decentrality Settings

Panwang Xia, Lei Yu, Yi Wan +12

Cross-View Geo-Localization tackles the challenge of image geo-localization in GNSS-denied environments, including disaster response scenarios, urban canyons, and dense forests, by…