activity
20152023
most citedFoveation-based Mechanisms Alleviate Adversarial Examples

137 citations · 394 across the 17 of their papers we have counts for

collaborators
Showing cs.CVShow all

12 papers · 1 filter

cs.CV2023

Iterative Robust Visual Grounding with Masked Reference based Centerpoint Supervision

Menghao Li, Chunlei Wang, Wenquan Feng +5

Visual Grounding (VG) aims at localizing target objects from an image based on given expressions and has made significant progress with the development of detection and vision tran…

cs.CV2023

Divide and Conquer: Answering Questions with Object Factorization and Compositional Reasoning

Shi Chen, Qi Zhao

Humans have the innate capability to answer diverse questions, which is rooted in the natural ability to correlate different concepts based on their semantic relationships and deco…

cs.CV2023★ 2 cited

Self-Training Guided Disentangled Adaptation for Cross-Domain Remote Sensing Image Semantic Segmentation

Qi Zhao, Shuchang Lyu, Binghao Liu +2

Deep convolutional neural networks (DCNNs) based remote sensing (RS) image semantic segmentation technology has achieved great success used in many real-world applications such as…

cs.CV2022

Look in Different Views: Multi-Scheme Regression Guided Cell Instance Segmentation

Menghao Li, Wenquan Feng, Shuchang Lyu +2

Cell instance segmentation is a new and challenging task aiming at joint detection and segmentation of every cell in an image. Recently, many instance segmentation methods have app…

cs.CV2021

Attention-based Feature Decomposition-Reconstruction Network for Scene Text Detection

Qi Zhao, Yufei Wang, Shuchang Lyu +1

Recently, scene text detection has been a challenging task. Texts with arbitrary shape or large aspect ratio are usually hard to detect. Previous segmentation-based methods can des…

cs.CV2021★ 1 cited

A Feature Consistency Driven Attention Erasing Network for Fine-Grained Image Retrieval

Qi Zhao, Xu Wang, Shuchang Lyu +2

Large-scale fine-grained image retrieval has two main problems. First, low dimensional feature embedding can fasten the retrieval process but bring accuracy reduce due to overlooki…

cs.CV2021★ 123 cited

TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios

Xingkui Zhu, Shuchang Lyu, Xu Wang +1

Object detection on drone-captured scenarios is a recent popular task. As drones always navigate in different altitudes, the object scale varies violently, which burdens the optimi…

cs.CV2021★ 30 cited

A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation

Qi Zhao, Binghao Liu, Shuchang Lyu +1

Few-shot segmentation focuses on the generalization of models to segment unseen object with limited annotated samples. However, existing approaches still face two main challenges.…

cs.CV2021★ 29 cited

Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification

Qi Zhao, Yujing Ma, Shuchang Lyu +1

Remote sensing (RS) image scene classification task faces many challenges due to the interference from different characteristics of different geographical elements. To solve this p…

cs.CV2020★ 8 cited

MM-FSOD: Meta and metric integrated few-shot object detection

Yuewen Li, Wenquan Feng, Shuchang Lyu +2

In the object detection task, CNN (Convolutional neural networks) models always need a large amount of annotated examples in the training process. To reduce the dependency of expen…

cs.CV2020★ 56 cited

MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification

Qi Zhao, Shuchang Lyu, Yuewen Li +2

Remote sensing (RS) scene classification is a challenging task to predict scene categories of RS images. RS images have two main characters: large intra-class variance caused by la…

cs.CV2019

Human Annotations Improve GAN Performances

Juanyong Duan, Sim Heng Ong, Qi Zhao

Generative Adversarial Networks (GANs) have shown great success in many applications. In this work, we present a novel method that leverages human annotations to improve the qualit…