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高校专区

Cornell University(康奈尔大学)

2026-02-06 至 2026-02-06 共收录 4
2505.16001 2026-02-06 cs.CV

Image-to-Image Translation with Diffusion Transformers and CLIP-Based Image Conditioning

基于扩散变换器和CLIP的图像到图像翻译

Qiang Zhu, Kuan Lu, Menghao Huo, Yuxiao Li

机构 * Department of Mechanical and Aerospace Engineering(机械与航空航天工程系) University of Houston(休斯顿大学) School of Engineering(工程学院) Santa Clara University(圣克拉拉大学) School of Electrical and Computer Engineering(电气与计算机工程学院) Cornell University(康奈尔大学) Department of Electrical and Computer Engineering(电气与计算机工程系) Northeastern University(东北大学)

AI总结 本文提出基于扩散变换器和CLIP的图像到图像翻译方法,通过CLIP嵌入引导实现高质量、语义一致的图像转换,为配对图像翻译任务提供新方案。

Comments Published in: 2025 6th International Conference on Computer Vision, Image and Deep Learning (CVIDL)

Journal ref 2025 6th International Conference on Computer Vision, Image and Deep Learning (CVIDL), pp. 626-632,

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2505.11620 2026-02-06 cs.CV cs.RO

Improved Bag-of-Words Image Retrieval with Geometric Constraints for Ground Texture Localization

改进的基于词袋的图像检索与几何约束用于地面纹理定位

Aaron Wilhelm, Nils Napp

机构 * School of Electrical and Computer Engineering, Cornell University(电气与计算机工程学院,康奈尔大学)

AI总结 本文提出改进的基于词袋的图像检索系统,利用几何约束提升地面纹理定位的全局定位准确性和SLAM回环检测的精度与召回率。

Comments Accepted to ICRA 2025

Journal ref Proc. IEEE Intl. Conf. Robot. Autom. (ICRA), pp. 8020-8026, 2025

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2602.05232 2026-02-06 cs.LG cs.AI

Balanced Anomaly-guided Ego-graph Diffusion Model for Inductive Graph Anomaly Detection

平衡的异常引导自环图扩散模型用于归纳图异常检测

Chunyu Wei, Siyuan He, Yu Wang, Yueguo Chen, Yunhai Wang, Bing Bai, Yidong Zhang, Yong Xie, Shunming Zhang, Fei Wang

机构 * Renmin University of China(中国人民大学) Independent Researcher(独立研究者) Microsoft(微软) Nanjing University of Posts and Telecommunications(南京邮电大学) Cornell University(康奈尔大学)

AI总结 本文提出一种平衡的异常引导自环图扩散模型,通过动态图建模和课程异常增强机制解决图异常检测中的动态性和类别不平衡问题。

Comments 12 pages,6 figures, Accepted by ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '26)

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2602.04926 2026-02-06 cs.DB cs.CL cs.LG

Pruning Minimal Reasoning Graphs for Efficient Retrieval-Augmented Generation

对检索增强生成进行最小推理图剪枝以提高效率

Ning Wang, Kuanyan Zhu, Daniel Yuehwoon Yee, Yitang Gao, Shiying Huang, Zirun Xu, Sainyam Galhotra

机构 * Cornell University(康奈尔大学) University of Cambridge(剑桥大学) The University of Hong Kong(香港大学) HKUST(香港科技大学) University of British Columbia(不列颠哥伦比亚大学)

AI总结 AutoPrunedRetriever通过最小推理图剪枝提升检索增强生成效率,实现更高效的知识密集型任务处理。

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