1.8k citations · 2k across the 6 of their papers we have counts for
6 papers
SEP-Attack: A Simple and Effective Paradigm for Transfer-Based Textual Adversarial Attack
Han Liu, Zhi Xu, Xiaotong Zhang +5
Despite the strong performance of deep neural networks in modern Web and language applications, they remain vulnerable to adversarial attacks, especially transferable attacks that…
HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
Han Liu, Jiaqi Li, Zhi Xu +5
Black-box adversarial attack on vision-language pre-trained models is a practical and challenging task, as text and image perturbations need to be considered simultaneously, and on…
EfficientRep:An Efficient Repvgg-style ConvNets with Hardware-aware Neural Network Design
Kaiheng Weng, Xiangxiang Chu, Xiaoming Xu +2
We present a hardware-efficient architecture of convolutional neural network, which has a repvgg-like architecture. Flops or parameters are traditional metrics to evaluate the effi…
YOLOv6 v3.0: A Full-Scale Reloading
Chuyi Li, Lulu Li, Yifei Geng +6
The YOLO community has been in high spirits since our first two releases! By the advent of Chinese New Year 2023, which sees the Year of the Rabbit, we refurnish YOLOv6 with numero…
Semi-MAE: Masked Autoencoders for Semi-supervised Vision Transformers
Haojie Yu, Kang Zhao, Xiaoming Xu
Vision Transformer (ViT) suffers from data scarcity in semi-supervised learning (SSL). To alleviate this issue, inspired by masked autoencoder (MAE), which is a data-efficient self…
YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications
Chuyi Li, Lulu Li, Hongliang Jiang +15
For years, the YOLO series has been the de facto industry-level standard for efficient object detection. The YOLO community has prospered overwhelmingly to enrich its use in a mult…