activity
20182023
most citedEvaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

158 citations · 195 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2023★ 2 cited

Fully Self-Supervised Depth Estimation from Defocus Clue

Haozhe Si, Bin Zhao, Dong Wang +4

Depth-from-defocus (DFD), modeling the relationship between depth and defocus pattern in images, has demonstrated promising performance in depth estimation. Recently, several self-…

cs.CL2020★ 1 cited

Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning

Xiaoxiao Guo, Mo Yu, Yupeng Gao +3

Interactive Fiction (IF) games with real human-written natural language texts provide a new natural evaluation for language understanding techniques. In contrast to previous text g…

cs.CV2019★ 27 cited

Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedback

Hui Wu, Yupeng Gao, Xiaoxiao Guo +4

Conversational interfaces for the detail-oriented retail fashion domain are more natural, expressive, and user friendly than classical keyword-based search interfaces. In this pape…

cs.CV2018★ 7 cited

Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

Dong Su, Huan Zhang, Hongge Chen +3

The prediction accuracy has been the long-lasting and sole standard for comparing the performance of different image classification models, including the ImageNet competition. Howe…

stat.ML2018★ 158 cited

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen +5

The robustness of neural networks to adversarial examples has received great attention due to security implications. Despite various attack approaches to crafting visually impercep…