8 citations · 10 across the 5 of their papers we have counts for
5 papers
CaFT: Clustering and Filter on Tokens of Transformer for Weakly Supervised Object Localization
Ming Li
Weakly supervised object localization (WSOL) is a challenging task to localize the object by only category labels. However, there is contradiction between classification and locali…
Automatic annotation of visual deep neural networks
Ming Li, ChenHao Guo
Computer vision is widely used in the fields of driverless, face recognition and 3D reconstruction as a technology to help or replace human eye perception images or multidimensiona…
A Data-Driven Method for Recognizing Automated Negotiation Strategies
Ming Li, Pradeep K. Murukannaiah, Catholijn M. Jonker
Understanding an opponent agent helps in negotiating with it. Existing works on understanding opponents focus on preference modeling (or estimating the opponent's utility function)…
Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps
Chaoyang He, Ming Li
The spatial anti-aliasing technique for line joins (intersections of the road segments) on vector maps is exclusively crucial to visual experience and system performance. Due to li…
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness
Lan-Zhe Guo, Yu-Feng Li, Ming Li +3
Weakly supervised data are widespread and have attracted much attention. However, since label quality is often difficult to guarantee, sometimes the use of weakly supervised data w…