4 citations · 21 across the 54 of their papers we have counts for
6 papers · 1 filter
Background Activation Suppression for Weakly Supervised Object Localization
Pingyu Wu, Wei Zhai, Yang Cao
Weakly supervised object localization (WSOL) aims to localize objects using only image-level labels. Recently a new paradigm has emerged by generating a foreground prediction map (…
On Exploring and Improving Robustness of Scene Text Detection Models
Shilian Wu, Wei Zhai, Yongrui Li +2
It is crucial to understand the robustness of text detection models with regard to extensive corruptions, since scene text detection techniques have many practical applications. Fo…
Learning Visual Affordance Grounding from Demonstration Videos
Hongchen Luo, Wei Zhai, Jing Zhang +2
Visual affordance grounding aims to segment all possible interaction regions between people and objects from an image/video, which is beneficial for many applications, such as robo…
One-Shot Object Affordance Detection in the Wild
Wei Zhai, Hongchen Luo, Jing Zhang +2
Affordance detection refers to identifying the potential action possibilities of objects in an image, which is a crucial ability for robot perception and manipulation. To empower r…
Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning
Kai Zhu, Yang Cao, Wei Zhai +2
Few-shot class-incremental learning is to recognize the new classes given few samples and not forget the old classes. It is a challenging task since representation optimization and…
One-Shot Affordance Detection
Hongchen Luo, Wei Zhai, Jing Zhang +2
Affordance detection refers to identifying the potential action possibilities of objects in an image, which is an important ability for robot perception and manipulation. To empowe…