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An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation
Bingyu Li, Da Zhang, Tao Huo +3
Large Vision-Language Models (LVLMs) have shown strong visual understanding and language-guided grounding abilities, yet their capacity for multi-temporal visual reasoning remains…
Towards Realistic Open-Vocabulary Remote Sensing Segmentation: Benchmark and Baseline
Bingyu Li, Tao Huo, Haocheng Dong +4
Open-vocabulary remote sensing image segmentation (OVRSIS) remains underexplored due to fragmented datasets, limited training diversity, and the lack of evaluation benchmarks that…
Reward-Aware Trajectory Shaping for Few-step Visual Generation
Rui Li, Bingyu Li, Yuanzhi Liang +3
Achieving high-fidelity generation in extremely few sampling steps has long been a central goal of generative modeling. Existing approaches largely rely on distillation-based frame…
Boosting Quantitive and Spatial Awareness for Zero-Shot Object Counting
Da Zhang, Bingyu Li, Feiyu Wang +2
Zero-shot object counting (ZSOC) aims to enumerate objects of arbitrary categories specified by text descriptions without requiring visual exemplars. However, existing methods ofte…
IntroSVG: Learning from Rendering Feedback for Text-to-SVG Generation via an Introspective Generator-Critic Framework
Feiyu Wang, Jiayuan Yang, Zhiyuan Zhao +4
Scalable Vector Graphics (SVG) are central to digital design due to their inherent scalability and editability. Despite significant advancements in content generation enabled by Vi…
Exploring the Underwater World Segmentation without Extra Training
Bingyu Li, Tao Huo, Da Zhang +3
Accurate segmentation of marine organisms is vital for biodiversity monitoring and ecological assessment, yet existing datasets and models remain largely limited to terrestrial sce…