From the 8 of 258 papers with an AI index.
134 citations
- University of Chinese Academy of SciencesCN66 papers
- Tsinghua UniversityCN63 papers
- Chinese Academy of SciencesCN60 papers
- University of Science and Technology of ChinaCN58 papers
- Nanjing UniversityCN54 papers
- Shanghai Jiao Tong UniversityCN54 papers
- Shandong UniversityCN48 papers
- Université Paris CitéFR47 papers
- Zhengzhou UniversityCN47 papers
- Chinese University of Hong KongHK43 papers
- University of Hong KongHK43 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di NapoliIT40 papers
17 papers · 1 filter
UniEvo-RS: Omni-Prompt Unified Remote Sensing Segmentation with Representative Exemplar-Driven Prototype Evolution
Kunquan Zhang, Peilang Li, Xikun Hu +4
Prompt-driven vision-language models (VLMs) hold immense promise for accelerating dense remote sensing (RS) annotation, but static models suffer from severe performance degradation…
Agentic Designer: Progressive Multi-Agent Collaboration for Structure-Aware Interior Layout Generation
Zhijing Yang, Haocheng Lin, Zhihua Xu +4
Generating realistic interior furniture layouts that strictly adhere to architectural constraints (e.g., walls, doors, and windows) remains a fundamental challenge in automated spa…
STAR: Skeletal Token Alignment and Rearrangement for Interaction Recognition
Yuhang Wen, Mengyuan Liu, Zixuan Tang +3
Understanding physical human-robot and human-human interactions is a challenging yet emerging topic in 3D vision. While most existing methods rely on skeleton sequences--effective…
Revisiting Shape and Texture Reliance with Category-Separability-Calibrated Suppression
Ning Jiang, Tianyi Luo, Zhengyong Huang +1
Feature-suppression evaluations infer model reliance on shape or texture from the accuracy loss caused by attenuating each type of information. Such losses, however, conflate featu…
Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective
Tianyuan Zhang, Xianglong Liu, Aishan Liu +6
Environmental illusions (eg., shadows, reflections, and tire marks) are naturally existing yet overlooked phenomena in real-world driving environments. They can disturb visual perc…
Learning Reference-Guided Exposure Correction with Hybrid Illumination Characteristics
Hao Ren, Zetong Bi, Zhaoliang Wan +1
We present HICNet, a reference-guided exposure correction framework. A lightweight, content-agnostic encoder distills each image into a compact illumination embedding capturing reg…