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20242026
most citedTowards Vision-Language Geo-Foundation Model: A Survey

6 citations · 6 across the 14 of their papers we have counts for

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cs.CV2026

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing

Zhaokai Wang, Mingxin Liu, Zirun Zhu +11

Recent image generation and editing models can produce visually appealing natural images, yet they remain unreliable when the target image is a knowledge-intensive diagram whose co…

cs.CV2026

GRADE: Benchmarking Discipline-Informed Reasoning in Image Editing

Mingxin Liu, Ziqian Fan, Zhaokai Wang +13

Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natural images and shallow commonsense…

cs.CV2026

Trust Your Critic: Robust Reward Modeling and Reinforcement Learning for Faithful Image Editing and Generation

Xiangyu Zhao, Peiyuan Zhang, Junming Lin +7

Reinforcement learning (RL) has emerged as a promising paradigm for enhancing image editing and text-to-image (T2I) generation. However, current reward models, which act as critics…

cs.CV2026

EvoTok: A Unified Image Tokenizer via Residual Latent Evolution for Visual Understanding and Generation

Yan Li, Ning Liao, Xiangyu Zhao +5

The development of unified multimodal large language models (MLLMs) is fundamentally challenged by the granularity gap between visual understanding and generation: understanding re…

cs.CV2026

CrossEarth-SAR: A SAR-Centric and Billion-Scale Geospatial Foundation Model for Domain Generalizable Semantic Segmentation

Ziqi Ye, Ziyang Gong, Ning Liao +10

Synthetic Aperture Radar (SAR) enables global, all-weather earth observation. However, owing to diverse imaging mechanisms, domain shifts across sensors and regions severely hinder…

cs.CV2026

Point2RBox-v3: Self-Bootstrapping from Point Annotations via Integrated Pseudo-Label Refinement and Utilization

Teng Zhang, Ziqian Fan, Mingxin Liu +8

Driven by the growing need for Oriented Object Detection (OOD), learning from point annotations under a weakly-supervised framework has emerged as a promising alternative to costly…