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20182023
most citedA Simple and Effective Pruning Approach for Large Language Models

53 citations · 121 across the 11 of their papers we have counts for

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8 papers · 1 filter

cs.CV2022

Fully and Weakly Supervised Referring Expression Segmentation with End-to-End Learning

Hui Li, Mingjie Sun, Jimin Xiao +2

Referring Expression Segmentation (RES), which is aimed at localizing and segmenting the target according to the given language expression, has drawn increasing attention. Existing…

cs.CV2021★ 2 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.CV2021★ 2 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.CV2020★ 1 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.CV2019★ 21 cited

Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach

Bingfeng Zhang, Jimin Xiao, Yunchao Wei +2

Weakly supervised semantic segmentation is a challenging task as it only takes image-level information as supervision for training but produces pixel-level predictions for testing.…