CVPR

ABBSPO: Adaptive Bounding Box Scaling and Symmetric Prior based Orientation Prediction for Detecting Aerial Image Objects

ABBSPO：自适应边界框缩放与对称先验的面向预测用于检测空中的图像对象

Woojin Lee, Hyugjae Chang, Jaeho Moon, Jaehyup Lee, Munchurl Kim

AI总结 ABBSPO通过自适应边界框缩放和对称先验角度损失，提升弱监督定向对象检测的准确性和效率。

Comments 17 pages, 11 figures, 8 tables, supplementary included. Accepted to CVPR 2025. Please visit our project page at https://kaist-viclab.github.io/ABBSPO_site/

ShapeWords: Guiding Text-to-Image Synthesis with 3D Shape-Aware Prompts

ShapeWords: 基于3D形状感知提示的文本到图像合成

Dmitry Petrov, Pradyumn Goyal, Divyansh Shivashok, Yuanming Tao, Melinos Averkiou, Evangelos Kalogerakis

机构 * UMass Amherst（马萨诸塞大学阿默斯特分校） ； CYENS CoE（CYENS联合学院） ； University of Cyprus（塞浦路斯大学） ； TU Crete（希腊技术大学） 纠错

AI总结 ShapeWords通过融合3D形状信息与文本提示，提升文本到图像合成的准确性与3D结构感知能力。

Comments Project webpage: https://lodurality.github.io/shapewords/ (CVPR 2025 paper), this Author Accepted Manuscript version is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) in accordance with the ERC / Horizon Europe open-access mandate