activity
20182021
most citedReliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach

21 citations · 26 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV20212 cited

Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding

Mingjie Sun, Jimin Xiao, Eng Gee Lim +2

In this paper, we are tackling the weakly-supervised referring expression grounding task, for the localization of a referent object in an image according to a query sentence, where…

cs.CV20212 cited

Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning

Mingjie Sun, Jimin Xiao, Eng Gee Lim

In this paper, we are tackling the proposal-free referring expression grounding task, aiming at localizing the target object according to a query sentence, without relying on off-t…

cs.CV2020

Extreme Value Preserving Networks

Mingjie Sun, Jianguo Li, Changshui Zhang

Recent evidence shows that convolutional neural networks (CNNs) are biased towards textures so that CNNs are non-robust to adversarial perturbations over textures, while traditiona…

cs.LG2020

Poisoned classifiers are not only backdoored, they are fundamentally broken

Mingjie Sun, Siddhant Agarwal, J. Zico Kolter

Under a commonly-studied backdoor poisoning attack against classification models, an attacker adds a small trigger to a subset of the training data, such that the presence of this…

cs.CV20201 cited

Fast Template Matching and Update for Video Object Tracking and Segmentation

Mingjie Sun, Jimin Xiao, Eng Gee Lim +2

In this paper, the main task we aim to tackle is the multi-instance semi-supervised video object segmentation across a sequence of frames where only the first-frame box-level groun…

cs.LG2020

Denoised Smoothing: A Provable Defense for Pretrained Classifiers

Hadi Salman, Mingjie Sun, Greg Yang +2

We present a method for provably defending any pretrained image classifier against adversarial attacks. This method, for instance, allows public vision API providers and u…