From the 1 of 1.6k papers with an AI index.
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- Peking UniversityCN495 papers
- Tsinghua UniversityCN356 papers
- Carnegie Mellon UniversityUS323 papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT319 papers
- University of Science and Technology of ChinaCN309 papers
- Institute of High Energy PhysicsCN298 papers
- University of Chinese Academy of SciencesCN283 papers
- Zhejiang UniversityCN273 papers
- Indian Institute of Technology MadrasIN272 papers
- University of PerugiaIT272 papers
- Institute of Modern PhysicsCN271 papers
- University of TurinIT267 papers
9 papers · 2 filters
Slow Motion Matters: A Slow Motion Enhanced Network for Weakly Supervised Temporal Action Localization
Weiqi Sun, Rui Su, Qian Yu +1
Weakly supervised temporal action localization (WTAL) aims to localize actions in untrimmed videos with only weak supervision information (e.g. video-level labels). Most existing m…
Synthetic Data Supervised Salient Object Detection
Zhenyu Wu, Lin Wang, Wei Wang +4
Although deep salient object detection (SOD) has achieved remarkable progress, deep SOD models are extremely data-hungry, requiring large-scale pixel-wise annotations to deliver su…
Salient Object Detection via Dynamic Scale Routing
Zhenyu Wu, Shuai Li, Chenglizhao Chen +2
Recent research advances in salient object detection (SOD) could largely be attributed to ever-stronger multi-scale feature representation empowered by the deep learning technologi…
Exploring Effective Knowledge Transfer for Few-shot Object Detection
Zhiyuan Zhao, Qingjie Liu, Yunhong Wang
Recently, few-shot object detection~(FSOD) has received much attention from the community, and many methods are proposed to address this problem from a knowledge transfer perspecti…
View-aware Salient Object Detection for 360° Omnidirectional Image
Junjie Wu, Changqun Xia, Tianshu Yu +1
Image-based salient object detection (ISOD) in 360° scenarios is significant for understanding and applying panoramic information. However, research on 360° ISOD has not been widel…
Look Before You Leap: Improving Text-based Person Retrieval by Learning A Consistent Cross-modal Common Manifold
Zijie Wang, Aichun Zhu, Jingyi Xue +4
The core problem of text-based person retrieval is how to bridge the heterogeneous gap between multi-modal data. Many previous approaches contrive to learning a latent common manif…