activity
20182026
most citedGenerative Adversarial Networks in Computer Vision: A Survey and Taxonomy

273 citations · 437 across the 16 of their papers we have counts for

collaborators

17 papers

cs.CV2026

SteerVTE: Seamless Video Text Editing with Style and Glyph Control

Kai Zeng, Moran Li, Zhengwei Wang +6

Visual text editing aims to precisely modify text in images and videos while preserving stylistic consistency and visual realism. Despite significant advances in the image domain,…

cs.CV2026

TextSculptor: Training and Benchmarking Scene Text Editing

Yiheng Lin, Siyu Jiao, Xiaohan Lan +12

Recent advances in Multimodal Large Language Models (MLLMs) and diffusion-based generative models have substantially improved prompt-driven image editing. However, scene text editi…

cs.LG2025

Exploring the Global-to-Local Attention Scheme in Graph Transformers: An Empirical Study

Gang Wu, Zhengwei Wang

Graph Transformers (GTs) show considerable potential in graph representation learning. The architecture of GTs typically integrates Graph Neural Networks (GNNs) with global attenti…

cs.CV2022★ 2 cited

MUSTER: A Multi-scale Transformer-based Decoder for Semantic Segmentation

Jing Xu, Wentao Shi, Pan Gao +2

In recent works on semantic segmentation, there has been a significant focus on designing and integrating transformer-based encoders. However, less attention has been given to tran…

cs.CV2021★ 4 cited

TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding

Zhengwei Wang, Qi She, Aljosa Smolic

Most of existing video action recognition models ingest raw RGB frames. However, the raw video stream requires enormous storage and contains significant temporal redundancy. Video…

cs.LG2021★ 46 cited

Generative adversarial networks in time series: A survey and taxonomy

Eoin Brophy, Zhengwei Wang, Qi She +1

Generative adversarial networks (GANs) studies have grown exponentially in the past few years. Their impact has been seen mainly in the computer vision field with realistic image a…

cs.CV2021★ 11 cited

ACTION-Net: Multipath Excitation for Action Recognition

Zhengwei Wang, Qi She, Aljosa Smolic

Spatial-temporal, channel-wise, and motion patterns are three complementary and crucial types of information for video action recognition. Conventional 2D CNNs are computationally…

cs.CV2020★ 2 cited

IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report

Qi She, Fan Feng, Qi Liu +33

This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top finalists (out of over~…

cs.CV2020★ 2 cited

CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition

Zhengwei Wang, Qi She, Tejo Chalasani +1

Egocentric gestures are the most natural form of communication for humans to interact with wearable devices such as VR/AR helmets and glasses. A major issue in such scenarios for r…

cs.CV2020★ 2 cited

A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Zhengwei Wang, Qi She, Alan F. Smeaton +2

Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. However, eva…

cs.CV2019★ 5 cited

OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning

Qi She, Fan Feng, Xinyue Hao +9

The recent breakthroughs in computer vision have benefited from the availability of large representative datasets (e.g. ImageNet and COCO) for training. Yet, robotic vision poses u…

cs.LG2019★ 273 cited

Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy

Zhengwei Wang, Qi She, Tomas E. Ward

Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably their most significant impact has been in the area of computer vision where gre…

cs.CV2019★ 5 cited

Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Zhengwei Wang, Qi She, Alan F. Smeaton +2

Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. Arguably the…

cs.LG2019★ 28 cited

Quick and Easy Time Series Generation with Established Image-based GANs

Eoin Brophy, Zhengwei Wang, Tomas E. Ward

In the recent years Generative Adversarial Networks (GANs) have demonstrated significant progress in generating authentic looking data. In this work we introduce our simple method…

eess.IV2019★ 11 cited

Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation

Zhengwei Wang, Graham Healy, Alan F. Smeaton +1

Rapid Serial Visual Presentation (RSVP) is a paradigm that supports the application of cortically coupled computer vision to rapid image search. In RSVP, images are presented to pa…

cs.CV2018★ 11 cited

An Interpretable Machine Vision Approach to Human Activity Recognition using Photoplethysmograph Sensor Data

Eoin Brophy, José Juan Dominguez Veiga, Zhengwei Wang +2

The current gold standard for human activity recognition (HAR) is based on the use of cameras. However, the poor scalability of camera systems renders them impractical in pursuit o…

cs.CV2018★ 35 cited

Use of Neural Signals to Evaluate the Quality of Generative Adversarial Network Performance in Facial Image Generation

Zhengwei Wang, Graham Healy, Alan F. Smeaton +1

There is a growing interest in using generative adversarial networks (GANs) to produce image content that is indistinguishable from real images as judged by a typical person. A num…