activity
20192022
most citedOn Exploring and Improving Robustness of Scene Text Detection Models

1 citations · 1 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV2022

Learning Affordance Grounding from Exocentric Images

Hongchen Luo, Wei Zhai, Jing Zhang +2

Affordance grounding, a task to ground (i.e., localize) action possibility region in objects, which faces the challenge of establishing an explicit link with object parts due to th…

cs.CV2022

Location-Free Camouflage Generation Network

Yangyang Li, Wei Zhai, Yang Cao +1

Camouflage is a common visual phenomenon, which refers to hiding the foreground objects into the background images, making them briefly invisible to the human eye. Previous work ha…

cs.CV2022

Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning

Kai Zhu, Wei Zhai, Yang Cao +2

Non-exemplar class-incremental learning is to recognize both the old and new classes when old class samples cannot be saved. It is a challenging task since representation optimizat…

cs.CV2022

Phrase-Based Affordance Detection via Cyclic Bilateral Interaction

Liangsheng Lu, Wei Zhai, Hongchen Luo +2

Affordance detection, which refers to perceiving objects with potential action possibilities in images, is a challenging task since the possible affordance depends on the person's…

cs.CV20211 cited

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…

cs.CV2021

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…