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cs.CV2026
Bootstrapping MLLM for Weakly-Supervised Class-Agnostic Object Counting
Xiaowen Zhang, Zijie Yue, Yong Luo +3
Object counting is a fundamental task in computer vision, with broad applicability in many real-world scenarios. Fully-supervised counting methods require costly point-level annota…
cs.CV2025
Text-promptable Object Counting via Quantity Awareness Enhancement
Miaojing Shi, Xiaowen Zhang, Zijie Yue +3
Recent advances in large vision-language models (VLMs) have shown remarkable progress in solving the text-promptable object counting problem. Representative methods typically speci…
cs.CV2025
TRAIL: Transferable Robust Adversarial Images via Latent diffusion
Yuhao Xue, Zhifei Zhang, Xinyang Jiang +6
Adversarial attacks exploiting unrestricted natural perturbations present severe security risks to deep learning systems, yet their transferability across models remains limited du…