4 papers
Aligning Few-Step Diffusion Models with Dense Reward Difference Learning
Ziyi Zhang, Li Shen, Sen Zhang +6
Few-step diffusion models enable efficient high-resolution image synthesis but struggle to align with specific downstream objectives due to limitations of existing reinforcement le…
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…
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…
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…