137 citations · 394 across the 17 of their papers we have counts for
17 papers
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…
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…
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…
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…
Learning to Predict Gradients for Semi-Supervised Continual Learning
Yan Luo, Yongkang Wong, Mohan Kankanhalli +1
A key challenge for machine intelligence is to learn new visual concepts without forgetting the previously acquired knowledge. Continual learning is aimed towards addressing this c…
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…
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…
Empirical Study of Named Entity Recognition Performance Using Distribution-aware Word Embedding
Xin Chen, Qi Zhao, Xinyang Liu
With the fast development of Deep Learning techniques, Named Entity Recognition (NER) is becoming more and more important in the information extraction task. The greatest difficult…
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…
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.…
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…
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…
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…
A Deep Learning Framework for Predicting Digital Asset Price Movement from Trade-by-trade Data
Qi Zhao
This paper presents a deep learning framework based on Long Short-term Memory Network(LSTM) that predicts price movement of cryptocurrencies from trade-by-trade data. The main focu…
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…
Dex: Incremental Learning for Complex Environments in Deep Reinforcement Learning
Nick Erickson, Qi Zhao
This paper introduces Dex, a reinforcement learning environment toolkit specialized for training and evaluation of continual learning methods as well as general reinforcement learn…
Foveation-based Mechanisms Alleviate Adversarial Examples
Yan Luo, Xavier Boix, Gemma Roig +2
We show that adversarial examples, i.e., the visually imperceptible perturbations that result in Convolutional Neural Networks (CNNs) fail, can be alleviated with a mechanism based…