activity
20212023
most citedCan CNNs Be More Robust Than Transformers?

15 citations · 35 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation

Zeyu Wang, Dingwen Li, Chenxu Luo +2

3D perception based on the representations learned from multi-camera bird's-eye-view (BEV) is trending as cameras are cost-effective for mass production in autonomous driving indus…

cs.CV2023★ 4 cited

CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a $10,000 Budget; An Extra $4,000 Unlocks 81.8% Accuracy

Xianhang Li, Zeyu Wang, Cihang Xie

The recent work CLIPA presents an inverse scaling law for CLIP training -- whereby the larger the image/text encoders used, the shorter the sequence length of image/text tokens tha…

cs.CV2023★ 8 cited

An Inverse Scaling Law for CLIP Training

Xianhang Li, Zeyu Wang, Cihang Xie

CLIP, one of the pioneering foundation models that connect images and text, has enabled many recent breakthroughs in computer vision. However, its associated training cost is prohi…

cs.CV2022★ 4 cited

Bag of Tricks for FGSM Adversarial Training

Zichao Li, Li Liu, Zeyu Wang +2

Adversarial training (AT) with samples generated by Fast Gradient Sign Method (FGSM), also known as FGSM-AT, is a computationally simple method to train robust networks. However, d…

cs.CV2022★ 2 cited

Masked Autoencoders Enable Efficient Knowledge Distillers

Yutong Bai, Zeyu Wang, Junfei Xiao +5

This paper studies the potential of distilling knowledge from pre-trained models, especially Masked Autoencoders. Our approach is simple: in addition to optimizing the pixel recons…

cs.CV2022★ 15 cited

Can CNNs Be More Robust Than Transformers?

Zeyu Wang, Yutong Bai, Yuyin Zhou +1

The recent success of Vision Transformers is shaking the long dominance of Convolutional Neural Networks (CNNs) in image recognition for a decade. Specifically, in terms of robustn…

cs.SE2021★ 1 cited

Plot2API: Recommending Graphic API from Plot via Semantic Parsing Guided Neural Network

Zeyu Wang, Sheng Huang, Zhongxin Liu +4

Plot-based Graphic API recommendation (Plot2API) is an unstudied but meaningful issue, which has several important applications in the context of software engineering and data visu…